Tootfinder

Biden had procedure to remove skin cancer from forehead (Brett Samuels/The Hill)
https://thehill.com/policy/healthcare/5487236-biden-procedure-skin-cancer-forehead/
http://www.memeorandum.com/250904/p152#a250904p152

Random thought: if a nuke plant worker has a nuclear medicine procedure done, do they have to stay home on medical leave until it's completely decayed/excreted or are there policies to handle hot employees?

A proposed U.S. federal rule change aims to limit international students (on visas) from spending longer than 4 years in the U.S..This would effectively ban international students from U.S. Ph.D. programs. Here is a link to the proposed rule change, including the ability to submit formal comments.
https://www.federalregister.gov/documents/2025/08/28/2025-16554/establishing-a-fixed-time-period-of-admission-and-an-extension-of-stay-procedure-for-nonimmigrant

Bootstrap Learning for Combinatorial Graph Alignment with Sequential GNNs
Marc Lelarge
https://arxiv.org/abs/2510.03086 https://arxiv.org/pdf/2510.03086

Bootstrap Learning for Combinatorial Graph Alignment with Sequential GNNs
Graph neural networks (GNNs) have struggled to outperform traditional optimization methods on combinatorial problems, limiting their practical impact. We address this gap by introducing a novel chaining procedure for the graph alignment problem, a fundamental NP-hard task of finding optimal node correspondences between unlabeled graphs using only structural information. Our method trains a sequence of GNNs where each network learns to iteratively refine similarity matrices produced by previous …

PentestMCP: A Toolkit for Agentic Penetration Testing
Zachary Ezetta, Wu-chang Feng
https://arxiv.org/abs/2510.03610 https://arxiv.org/pdf/2510.03610

PentestMCP: A Toolkit for Agentic Penetration Testing
Agentic AI is transforming security by automating many tasks being performed manually. While initial agentic approaches employed a monolithic architecture, the Model-Context-Protocol has now enabled a remote-procedure call (RPC) paradigm to agentic applications, allowing for the flexible construction and composition of multi-function agents. This paper describes PentestMCP, a library of MCP server implementations that support agentic penetration testing. By supporting common penetration testing…

Using Gauge Covariant Lie Derivatives in Einstein-Cartan and Metric Teleparallel Theories of Gravity
R. J. van den Hoogen, H. Forance, L. Taylor, M. Lawton
https://arxiv.org/abs/2510.03082

Using Gauge Covariant Lie Derivatives in Einstein-Cartan and Metric Teleparallel Theories of Gravity
A procedure to determine the initial ansatz for the co-frame and spin connection characterizing a Riemann-Cartan geometry respecting a given group of continuous symmetries is illustrated. Given a particular group of symmetries and assuming an orthonormal gauge we can determine the co-frame and corresponding spin connection having this symmetry group by employing an gauge covariant Lie derivative. This gauge covariant Lie derivative when applied to the metric and co-frame determines the values o…

An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory
Christopher Leet, Aidan Sciortino, Sven Koenig
https://arxiv.org/abs/2510.01770

An Anytime, Scalable and Complete Algorithm for Embedding a Manufacturing Procedure in a Smart Factory
Modern automated factories increasingly run manufacturing procedures using a matrix of programmable machines, such as 3D printers, interconnected by a programmable transport system, such as a fleet of tabletop robots. To embed a manufacturing procedure into a smart factory, an operator must: (a) assign each of its processes to a machine and (b) specify how agents should transport parts between machines. The problem of embedding a manufacturing process into a smart factory is termed the Smart Fa…

Mutual Information-Driven Visualization and Clustering for Core KPI Selection in O-RAN Testing
Anish Pradhan, Lingjia Liu, Harpreet S. Dhillon
https://arxiv.org/abs/2510.02696 h…

Mutual Information-Driven Visualization and Clustering for Core KPI Selection in O-RAN Testing
O-RAN testing is becoming increasingly difficult with the exponentially growing number of performance measurements as the system grows more complex, with additional units, interfaces, applications, and possible implementations and configurations. To simplify the testing procedure and improve system design for O-RAN systems, it is important to identify the dependencies among various performance measurements, which are inherently time-series and can be modeled as realizations of random processes.…

Updated Radio Sigma-D Relation and Distances to the Shell-Like Galactic Supernova Remnants -- IV
D. Uro\v{s}evi\'c, B. Vukoti\'c, M. An{\dj}eli\'c, N. Mladenovi\'c
https://arxiv.org/abs/2510.03410

Updated Radio Sigma-D Relation and Distances to the Shell-Like Galactic Supernova Remnants -- IV
We present a new selected sample of 69 Galactic supernova remnants (SNRs) for calibration of radio $Σ-D$ relation at 1 GHz. Calibrators with the most reliable distances were selected through an extensive literature search. The calibration is performed using kernel smoothing of the selected sample of calibrators in $Σ-D$ plane and an orthogonal offsets fitting procedure. We use the obtained calibration to derive the distances to 164 Galactic SNRs and 27 new detected SNRs/SNR candidates with no…

Decision Procedure for A Theory of String Sequences
Denghang Hu, Taolue Chen, Philipp R\"ummer, Fu Song, Zhilin Wu
https://arxiv.org/abs/2509.00948 https://

Decision Procedure for A Theory of String Sequences
The theory of sequences, supported by many SMT solvers, can model program data types including bounded arrays and lists. Sequences are parameterized by the element data type and provide operations such as accessing elements, concatenation, forming sub-sequences and updating elements. Strings and sequences are intimately related; many operations, e.g., matching a string according to a regular expression, splitting strings, or joining strings in a sequence, are frequently used in string-manipulat…

Fins WR Hill practices; RB Wright has procedure https://www.espn.com/nfl/story/_/id/46096191/tyreek-hill-back-practice-rb-jaylen-wright-leg-procedure

Pure many-body interactions in colloidal systems by artificial random light fields
Augustin Muster, Luis S. Froufe-P\'erez
https://arxiv.org/abs/2510.03503 https://

Pure many-body interactions in colloidal systems by artificial random light fields
We propose a method to generate pure many-body interactions in colloidal systems by using optical forces induced by random optical fields with an optimized spectral energy density. To assess the feasibility in general settings, we develop a simple model for Lorentzian electric and magnetic dipole response. An optimization procedure is then introduced to design the spectral energy density of the random field that minimizes pair interactions at constant electromagnetic energy density. We conclude…

An Agentic Model Context Protocol Framework for Medical Concept Standardization
Jaerong Ahn, Andrew Wen, Nan Wang, Heling Jia, Zhiyi Yue, Sunyang Fu, Hongfang Liu
https://arxiv.org/abs/2509.03828

An Agentic Model Context Protocol Framework for Medical Concept Standardization
The Observational Medical Outcomes Partnership (OMOP) common data model (CDM) provides a standardized representation of heterogeneous health data to support large-scale, multi-institutional research. One critical step in data standardization using OMOP CDM is the mapping of source medical terms to OMOP standard concepts, a procedure that is resource-intensive and error-prone. While large language models (LLMs) have the potential to facilitate this process, their tendency toward hallucination ma…

Qubit-optimal quantum phase estimation of block-encoded Hamiltonians
S. E. Skelton
https://arxiv.org/abs/2509.04246 https://arxiv.org/pdf/2509.04246…

Qubit-optimal quantum phase estimation of block-encoded Hamiltonians
Block-encodings have become one of the most common oracle assumptions in the circuit model. I present an algorithm that uses von Neumann's measurement procedure to measure a phase, using time evolution on a block-encoded Hamiltonian as a subroutine. This produces an extremely simple algorithm for quantum phase estimation, which can be performed with a pointer system of $\mathcal{O}(1)$ qubits. I then use recent results for block-encoding implementations, showing that one can efficiently prepa…

Bootstrapping as a Morphism: An Arithmetic Geometry Approach to Asymptotically Faster Homomorphic Encryption
Dongfang Zhao
https://arxiv.org/abs/2510.02365 https://

Bootstrapping as a Morphism: An Arithmetic Geometry Approach to Asymptotically Faster Homomorphic Encryption
Fully Homomorphic Encryption (FHE) provides a powerful paradigm for secure computation, but its practical adoption is severely hindered by the prohibitive computational cost of its bootstrapping procedure. The complexity of all current bootstrapping methods is fundamentally tied to the multiplicative depth of the decryption circuit, denoted $L_{dec}$, making it the primary performance bottleneck. This paper introduces a new approach to bootstrapping that completely bypasses the traditional circ…

An iterated $I$-projection procedure for solving the generalized minimum information checkerboard copula problem
Ivan Kojadinovic, Tommaso Martini
https://arxiv.org/abs/2509.02829

An iterated $I$-projection procedure for solving the generalized minimum information checkerboard copula problem
The minimum information copula principle initially suggested in \cite{MeeBed97} is a maximum entropy-like approach for finding the least informative copula, if it exists, that satisfies a certain number of expectation constraints specified either from domain knowledge or the available data. We first propose a generalization of this principle allowing the inclusion of additional constraints fixing certain higher-order margins of the copula. We next show that the associated optimization problem h…

Judge Jia M. Cobb rejected what she called
“a truly startling argument”
from the government
that it could use a fast-track procedure to remove people arrested far from the southern border.
The case focused on a policy shift announced during the first week of Trump’s second term
that authorized the Department of Homeland Security to launch quick deportations,
across the country and without court proceedings,
of undocumented immigrants who cannot prove…

Judge Blocks Pillar of Trump’s Mass Deportation Campaign
Judge Jia M. Cobb rejected what she called “a truly startling argument” from the government that it could use a fast-track procedure to remove people arrested far from the southern border.

Perceptual Evaluation of Extrapolated Spatial Room Impulse Responses From a Mono Source
Ben Heritage, Fiona Ryder, Michael McLoughlin, Karolina Prawda
https://arxiv.org/abs/2510.04937

Perceptual Evaluation of Extrapolated Spatial Room Impulse Responses From a Mono Source
Immersion in virtual and augmented reality solutions is reliant on plausible spatial audio. However, plausibly representing a space for immersive audio often requires many individual acoustic measurements of source-microphone pairs with specialist spatial microphones, making the procedure time-consuming and expensive. In this study, we evaluate the plausibility of extrapolated and spatialised Room Impulse Responses (RIRs) by using a 3-Alternative Forced Choice (3AFC) listening test. The stimuli…

So the US hit a Venezuelan drugs vessel and killed 11 people aboard. This way of operating against a ship is so illegal it hurts. No judge, no procedure, just killing...
https://www.cnn.com/2025/09/02/politics/us-military-strike-caribbean

US military kills 11 in strike on alleged drug boat tied to Venezuelan cartel, Trump says
The United States conducted a deadly military strike against an alleged drug boat tied to the cartel Tren de Aragua, President Donald Trump said Tuesday.

Today I had to go to the dentist, to have a filling replaced. My dentist is a small young woman from Glasgow, very competent, who chats cheerily through the whole procedure.
But I was thinking of @… , a poet from #Gaza who wants to be a dentist, and wh…

Urgent help for Ahmed's family
"I’m tired, Mama. I’m thinking of the hours that I'll spend tomorrow in the water line." – says 9 year old Ahmed to his mother before going to sleep.

An alternative bootstrap procedure for factor-augmented regression models
Peiyun Jiang, Takashi Yamagata
https://arxiv.org/abs/2510.00947 https://arxiv.org…

An alternative bootstrap procedure for factor-augmented regression models
In this paper, we propose a novel bootstrap algorithm that is more efficient than existing methods for approximating the distribution of the factor-augmented regression estimator for a rotated parameter vector. The regression is augmented by $r$ factors extracted from a large panel of $N$ variables observed over $T$ time periods. We consider general weak factor (WF) models with $r$ signal eigenvalues that may diverge at different rates, $N^{α_{k}}$, where $0<α_{k}\leq 1$ for $k=1,2,...,r$. We…

Parameter Tuning Under Uncertain Road Perception in Driver Assistance Systems
Leon Greiser, Christian Rathgeber, Vladislav Nenchev, S\"oren Hohmann
https://arxiv.org/abs/2509.03694

Parameter Tuning Under Uncertain Road Perception in Driver Assistance Systems
Advanced driver assistance systems have improved comfort, safety, and efficiency of modern vehicles. However, sensor limitations lead to noisy lane estimates that pose a significant challenge in developing performant control architectures. Lateral trajectory planning often employs an optimal control formulation to maintain lane position and minimize steering effort. The parameters are often tuned manually, which is a time-intensive procedure. This paper presents an automatic parameter tuning me…

Vulnerability Analysis Evaluating Bilevel Optimal Power Flow Approaches for Multiple Load Cases
Eric T\"onges, Martin Braun, Philipp H\"artel
https://arxiv.org/abs/2510.01073

Vulnerability Analysis Evaluating Bilevel Optimal Power Flow Approaches for Multiple Load Cases
This work presents two methodologies to enhance vulnerability assessment in power systems using bilevel attacker-defender network interdiction models. First, we introduce a systematic evaluation procedure for comparing different optimal power flow formulations in the lower-level problem. We demonstrate the procedure for a comparison of the widely used DC approximation and a linearized AC optimal power flow model. Second, we propose a novel scoring methodology to identify and prioritize critical…

Two Optimizations on the St\aa lmarck Procedure
Sergei Leonov, Liam Davis
https://arxiv.org/abs/2509.16172 https://arxiv.org/pdf/2509.16172

Two Optimizations on the Stålmarck Procedure
In this paper, we introduce StalmarckSAT, the a modern re-implementation of the Stålmarck Procedure for SAT solving, and present two novel strategies to improve the Procedure, Cardinality Driven Branching (CDB) and Deductive Priority Ordering (DPO). CDB is a heuristic to improve branching with the dilemma rule, and DPO intelligently orders simple rules based on their deductive potential. Our results demonstrate improved solve times with both strategies.

Dulin, S., Mitoulis, SA., Bredikhin, A. et al. 3 November 2025
"Rethinking infrastructure design from component failure to systemic resilience."
Nature Communications 16, 9681 (2025).
https://doi.org/10.1038/s41467-025-64683-6
pdf:

Energy Confinement Time Scaling for the Negative Triangularity Scenario in DIII-D
P. Lunia
https://arxiv.org/abs/2509.04279 https://arxiv.org/pdf/2509.0427…

Energy Confinement Time Scaling for the Negative Triangularity Scenario in DIII-D
Results from the 2023 negative triangularity campaign on DIII-D demonstrate encouraging energy confinement properties, similar to or exceeding the scaling of the IPB98(y,2) law. This paper describes the procedure with which a new scaling law was regressed specifically from the data from the DIII-D campaign. Given the relatively small size of the single-machine dataset, measures were taken to minimize sampling bias and give a realistic estimate of the large uncertainties from the regression. The…

AdS$_7$ Black Holes and Holography
Nikolay Bobev, Marina David, Vasil Dimitrov, Junho Hong
https://arxiv.org/abs/2509.02833 https://arxiv.org/pdf/2509.0283…

AdS$_7$ Black Holes and Holography
We present a detailed study of the regularized on-shell action of the recently found asymptotically AdS$_7$ black hole supergravity solution with three angular momenta and two electric charges. We show that a particular choice of finite counterterms in the holographic renormalization procedure yields a result for the on-shell action of the supersymmetric limit of the black hole solution which is in perfect agreement with the large $N$ limit of the superconformal index of the dual 6d $\mathcal{N…

How to invert well-pointed endofunctors
Matt Booth
https://arxiv.org/abs/2510.02277 https://arxiv.org/pdf/2510.02277

How to invert well-pointed endofunctors
In this short note we observe that Kelly's transfinite construction of free algebras yields a way to invert well-pointed endofunctors. In enriched settings, this recovers constructions of Keller, Seidel, and Chen-Wang. We also relate this procedure to localisation by spectra and to Heller's stabilisation.

Sources: Chargers' Alt may need ankle procedure https://www.espn.com/nfl/story/_/id/46822922/sources-chargers-alt-dealing-another-high-ankle-sprain

Two-flavor chirally imbalanced quark matter beyond large-$N_c$
Andr\'e G. da Silva, Dyana C. Duarte, Ricardo L. S. Farias, Marcus Benghi Pinto, Rudnei O. Ramos, William R. Tavares
https://arxiv.org/abs/2509.02955

Two-flavor chirally imbalanced quark matter beyond large-$N_c$
We investigate a chirally imbalanced medium in the context of the two-flavor Nambu--Jona-Lasinio model using both the large-$N_c$ (LN) and beyond large-$N_c$ (BLN) approximations. To incorporate BLN effects, we consider the optimized perturbation theory (OPT) to the first nontrivial order, which includes two-loop (exchange) contributions. This procedure allows us to explicitly explore how finite $N_c$ corrections affect the thermodynamics as well as the phase diagram of chirally imbalanced quar…

Wild Refitting for Model-Free Excess Risk Evaluation of Opaque ML/AI Models under Bregman Loss
Haichen Hu, David Simchi-Levi
https://arxiv.org/abs/2509.02476 https://

Wild Refitting for Model-Free Excess Risk Evaluation of Opaque ML/AI Models under Bregman Loss
We study the problem of evaluating the excess risk of classical penalized empirical risk minimization (ERM) with Bregman losses. We show that by leveraging the recently proposed wild refitting procedure (Wainwright, 2025), one can efficiently upper bound the excess risk through the so-called "wild optimism," without relying on the global structure of the underlying function class. This property makes our approach inherently model-free. Unlike conventional analyses, our framework operates with j…

Series B, Episode 10 - Voice from the Past
BLAKE: Guilty.
ORAC: No. Conditioned under hypnosis.
BLAKE: No. No.
ORAC: Yes, Blake. Standard hypnotic procedure, audio pulse signals with visual support...
BLAKE: False.
https://blake.torpidity.net/m/210/139 B7B6

Neural Posterior Estimation with Autoregressive Tiling for Detecting Objects in Astronomical Images
Jeffrey Regier
https://arxiv.org/abs/2510.03074 https://

Neural Posterior Estimation with Autoregressive Tiling for Detecting Objects in Astronomical Images
Upcoming astronomical surveys will produce petabytes of high-resolution images of the night sky, providing information about billions of stars and galaxies. Detecting and characterizing the astronomical objects in these images is a fundamental task in astronomy -- and a challenging one, as most of these objects are faint and many visually overlap with other objects. We propose an amortized variational inference procedure to solve this instance of small-object detection. Our key innovation is a …

CVSM: Contrastive Vocal Similarity Modeling
Christos Garoufis, Athanasia Zlatintsi, Petros Maragos
https://arxiv.org/abs/2510.03025 https://arxiv.org/pdf/2…

CVSM: Contrastive Vocal Similarity Modeling
The availability of large, unlabeled datasets across various domains has contributed to the development of a plethora of methods that learn representations for multiple target (downstream) tasks through self-supervised pre-training. In this work, we introduce CVSM (Contrastive Vocal Similarity Modeling), a contrastive self-supervised procedure for music signal representation learning in the audio domain that can be utilized for musical and vocal similarity modeling. Our method operates under a …

Sequential Change Detection with Differential Privacy
Liyan Xie, Ruizhi Zhang
https://arxiv.org/abs/2509.02768 https://arxiv.org/pdf/2509.02768

Sequential Change Detection with Differential Privacy
Sequential change detection is a fundamental problem in statistics and signal processing, with the CUSUM procedure widely used to achieve minimax detection delay under a prescribed false-alarm rate when pre- and post-change distributions are fully known. However, releasing CUSUM statistics and the corresponding stopping time directly can compromise individual data privacy. We therefore introduce a differentially private (DP) variant, called DP-CUSUM, that injects calibrated Laplace noise into b…

Newton-Flow Particle Filters based on Generalized Cram\'er Distance
Uwe D. Hanebeck
https://arxiv.org/abs/2509.00182 https://arxiv.org/pdf/2509.00182…

Newton-Flow Particle Filters based on Generalized Cramér Distance
We propose a recursive particle filter for high-dimensional problems that inherently never degenerates. The state estimate is represented by deterministic low-discrepancy particle sets. We focus on the measurement update step, where a likelihood function is used for representing the measurement and its uncertainty. This likelihood is progressively introduced into the filtering procedure by homotopy continuation over an artificial time. A generalized Cramér distance between particle sets is der…

Optimization procedure of the baffle of the GroundBIRD Telescope to mitigate stray light
Miku Tsujii, Tomonaga Tanaka, Alessandro Fasano, Ricardo G\'enova-Santos, Shunsuke Honda, Yonggil Jo, Keisuke Kataoka, Chiko Otani, Mike Peel, Junya Suzuki, Osamu Tajima, Eunil Won, Makoto Hattori
https://arxiv.org/abs/2509.22071

Optimization procedure of the baffle of the GroundBIRD Telescope to mitigate stray light
We presented the optimization procedures of the baffle mounted on the GroundBIRD telescope for measuring the polarization of the Cosmic Microwave Background~(CMB). The telescope employs dual mirror reflective telescopes installed in a cryostat. The primary objectives were to minimize stray light contamination, maintain the integrity of the main beam, and ensure that thermal loading from the baffle remains significantly below that from the atmosphere. Using quasi-optical simulations, we have opt…

FLOWER: A Flow-Matching Solver for Inverse Problems
Mehrsa Pourya, Bassam El Rawas, Michael Unser
https://arxiv.org/abs/2509.26287 https://arxiv.org/pdf/25…

FLOWER: A Flow-Matching Solver for Inverse Problems
We introduce Flower, a solver for inverse problems. It leverages a pre-trained flow model to produce reconstructions that are consistent with the observed measurements. Flower operates through an iterative procedure over three steps: (i) a flow-consistent destination estimation, where the velocity network predicts a denoised target; (ii) a refinement step that projects the estimated destination onto a feasible set defined by the forward operator; and (iii) a time-progression step that re-projec…

Hecke modifications of conformal blocks outside the critical level
Raschid Abedin, Giovanni Felder, Robert Windesheim
https://arxiv.org/abs/2509.02368 https://

Hecke modifications of conformal blocks outside the critical level
We define Hecke modifications of conformal blocks over affine Lie algebras at non-critical level by using the Hecke modifications of the underlying $G$-bundles. We show that this procedure is equivalent to the insertion of a twisted vacuum module at an additional marked point and provide an explicit description using coordinate transformations.

Jaylen Wright injury update: Dolphins RB expected to miss multiple weeks after undergoing procedure on his leg

https://www.cbssports.com/nfl/news/jayle…

A QoS Framework for Service Provision in Multi-Infrastructure-Sharing Networks
Quang Minh Nguyen, Eytan Modiano
https://arxiv.org/abs/2509.01694 https://ar…

A QoS Framework for Service Provision in Multi-Infrastructure-Sharing Networks
We propose a framework for resource provisioning with QoS guarantees in shared infrastructure networks. Our novel framework provides tunable probabilistic service guarantees for throughput and delay. Key to our approach is a Modified Dirft-plus-Penalty (MDP) policy that ensures long-term stability while capturing short-term probabilistic service guarantees using linearized upper-confidence bounds. We characterize the feasible region of service guarantees and show that our MDP procedure achieves…

Interesting way to represent uncertain or vague information into #knowledgegraphs (as e.g. easier integration of LLM/Deep Learning Results into KGs) via "Fuzzy OWL". Paper by Fernando Bobillo & Umberto Straccia: Fuzzy Ontology Representation using OWL 2

Fuzzy Ontology Representation using OWL 2
The need to deal with vague information in Semantic Web languages is rising in importance and, thus, calls for a standard way to represent such information. We may address this issue by either extending current Semantic Web languages to cope with vagueness, or by providing a procedure to represent such information within current standard languages and tools. In this work, we follow the latter approach, by identifying the syntactic differences that a fuzzy ontology language has to cope with, and…

Public hospital procedure for gastroscopy and colonoscopy. Husband is on a disability pension but that is not relevant in this case.
Obviously he has to take the prep beforehand - which he needs to get from a chemist as TCH no longer supplies it as part of the procedure??? - and it costs about $39 for the 3 sachets he has to take beforehand.
Okay, now we can afford this but it seems to me that it could be quite a stumbling block for those who can't.
Don't get me w…

"Any tutorial on how to set it up currently?"
I've got you. Just follow these simple instructions.

Spectral Bootstrap for Non-Parametric Simulation of Multivariate Extreme Events
Nisrine Madhar (UPCit\'e, LPSM), Juliette Legrand (LMBA, UBO), Maud Thomas (LPSM)
https://arxiv.org/abs/2509.26451

Spectral Bootstrap for Non-Parametric Simulation of Multivariate Extreme Events
Inference in extreme value theory relies on a limited number of extreme observations, making estimation challenging. To address this limitation, we propose a non-parametric bootstrap procedure, the multivariate extreme spectral bootstrap procedure, relying on the spectral representation of multivariate generalized Paretodistributed random vectors. Unlike standard bootstrap methods, our approach preserves the joint tail behaviour of the data and generates additional synthetic extreme data, there…

WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures
Faraz Faruqi, Josha Paonaskar, Riley Schuler, Aiden Prevey, Carson Taylor, Anika Tak, Anthony Guinto, Eeshani Shilamkar, Natarith Cheenaruenthong, Martin Nisser
https://arxiv.org/abs/2509.24083…

WireBend-kit: A Computational Design and Fabrication Toolkit for Wirebending Custom 3D Wireframe Structures
This paper introduces WireBend-kit, a desktop wirebending machine and computational design tool for creating 3D wireframe structures. Combined, they allow users to rapidly and inexpensively create custom 3D wireframe structures from aluminum wire. Our design tool is implemented in freely available software and allows users to generate virtual wireframe designs and assess their fabricability. A path-planning procedure automatically converts the wireframe design into fabrication instructions for …

Approximate constrained stochastic optimal control via parameterized input inference
Shahbaz P Qadri Syed, He Bai
https://arxiv.org/abs/2509.02922 https://…

Approximate constrained stochastic optimal control via parameterized input inference
Approximate methods to solve stochastic optimal control (SOC) problems have received significant interest from researchers in the past decade. Probabilistic inference approaches to SOC have been developed to solve nonlinear quadratic Gaussian problems. In this work, we propose an Expectation-Maximization (EM) based inference procedure to generate state-feedback controls for constrained SOC problems. We consider the inequality constraints for the state and controls and also the structural constr…

A reproducible comparative study of categorical kernels for Gaussian process regression, with new clustering-based nested kernels
Rapha\"el Carpintero Perez (CMAP), S\'ebastien Da Veiga (ENSAI, CREST, RT-UQ), Josselin Garnier (CMAP, ASCII)
https://arxiv.org/abs/2510.01840

A reproducible comparative study of categorical kernels for Gaussian process regression, with new clustering-based nested kernels
Designing categorical kernels is a major challenge for Gaussian process regression with continuous and categorical inputs. Despite previous studies, it is difficult to identify a preferred method, either because the evaluation metrics, the optimization procedure, or the datasets change depending on the study. In particular, reproducible code is rarely available. The aim of this paper is to provide a reproducible comparative study of all existing categorical kernels on many of the test cases inv…

Linking Path-Dependent and Stochastic Volatility Models
Samuel N. Cohen, Cephas Svosve
https://arxiv.org/abs/2510.02024 https://arxiv.org/pdf/2510.02024

Linking Path-Dependent and Stochastic Volatility Models
We explore a link between stochastic volatility (SV) and path-dependent volatility (PDV) models. Using assumed density filtering, we map a given SV model into a corresponding PDV representation. The resulting specification is lightweight, improves in-sample fit, and delivers robust out-of-sample forecasts. We also introduce a calibration procedure for both SV and PDV models that produces standard errors for parameter estimates and supports joint calibration of SPX/VIX smile.

Deficiency of equation-finding approach to data-driven modeling of dynamical systems
Zheng-Meng Zhai, Valerio Lucarini, Ying-Cheng Lai
https://arxiv.org/abs/2509.03769 https://

Deficiency of equation-finding approach to data-driven modeling of dynamical systems
Finding the governing equations from data by sparse optimization has become a popular approach to deterministic modeling of dynamical systems. Considering the physical situations where the data can be imperfect due to disturbances and measurement errors, we show that for many chaotic systems, widely used sparse-optimization methods for discovering governing equations produce models that depend sensitively on the measurement procedure, yet all such models generate virtually identical chaotic att…

Machine-precision energy conservative quadrature hyperreduction of Lagrangian hydrodynamics
Chris Vales, Siu Wun Cheung, Dylan M. Copeland, Youngsoo Choi
https://arxiv.org/abs/2508.21279

Machine-precision energy conservative quadrature hyperreduction of Lagrangian hydrodynamics
We present an energy conservative, quadrature based model reduction framework for the compressible Euler equations of Lagrangian hydrodynamics. Building on a high order finite element discretization of the governing equations, we develop a projection based reduced model using data driven reduced basis functions and hyperreduction via the empirical quadrature procedure (EQP). We introduce a strongly energy conservative variant of EQP that enforces exact discrete total energy conservation during …

Steady Gradient Ricci Solitons with $O(p)\times O(q)$ Symmetry
Lucas Lavoyer, Luke T. Peachey
https://arxiv.org/abs/2509.25081 https://arxiv.org/pdf/2509.2…

Steady Gradient Ricci Solitons with $O(p)\times O(q)$ Symmetry
We find new examples of steady gradient Ricci solitons with positive curvature operator in dimensions four and above. Utilising a procedure first introduced by Lai, we construct examples with $O(p) \times O(q)$ symmetry in dimension $p+q$ for any pair of integers $p,q \geq 2$ and discuss their asymptotic geometry.

Phase spaces in field theory: Reduction vs. resolution
Aldo Riello, Michele Schiavina
https://arxiv.org/abs/2509.24450 https://arxiv.org/pdf/2509.24450

Phase spaces in field theory: Reduction vs. resolution
In this note we review the concept of phase space in classical field theory, discussing several variations on the basic notion, as well as the relation between them. In particular we will focus on the case where the field theory admits local (gauge) symmetry, in which case the physical phase space of the system emerges after a (usually singular) quotient with respect to the action of the symmetry group. We will highlight the symplectic and Poisson underpinnings of the reduction procedure that d…

There actually is good news - which we shouldn't forget.
https://www.theguardian.com/science/2025/sep/24/huntingtons-disease-treated-successfully-for-first-time-in-gene-therapy-trial…

There actually is good news - which we shouldn't forget.
https://www.theguardian.com/science/2025/sep/24/huntingtons-disease-treated-successfully-for-first-time-in-gene-therapy-trial…

Resolving features and derivatives in data with noise
L. (Bert), Mulder, Ad Lagendijk, Willem L. Vos
https://arxiv.org/abs/2509.22077 https://arxiv.org/pd…

Resolving features and derivatives in data with noise
A frequently occurring challenge in experimental and numerical observation is how to resolve features, such as spectral peaks - with center, width, height - and derivatives from measured data with unavoidable noise. Therefore, we develop a modified Whittaker-Henderson smoothing procedure that balances the spectral features and the noise. In our procedure, we introduce adjustable weights that are optimized using cross-validation. When the measurement errors are known, a straightforward error ana…

Joint Inference for the Regression Discontinuity Effect and Its External Validity
Yuta Okamoto
https://arxiv.org/abs/2509.26380 https://arxiv.org/pdf/2509.…

Joint Inference for the Regression Discontinuity Effect and Its External Validity
The external validity of regression discontinuity (RD) designs is essential for informing policy and remains an active research area in econometrics and statistics. However, we document that only a limited number of empirical studies explicitly address the external validity of standard RD effects. To advance empirical practice, we propose a simple joint inference procedure for the RD effect and its local external validity, building on Calonico, Cattaneo, and Titiunik (2014, Econometrica) and Do…

A note on a resampling procedure for estimating the density at a given quantile
Beatriz Farah (MAP5 - UMR 8145), Aur\'elien Latouche (CNAM Paris), Olivier Bouaziz (LPP, MAP5 - UMR 8145)
https://arxiv.org/abs/2509.02207

A note on a resampling procedure for estimating the density at a given quantile
In this paper we refine the procedure proposed by Lin et al. (2015) to estimate the density at a given quantile based on a resampling method. The approach consists on generating multiple samples of the zero-mean Gaussian variable from which a least square estimator is constructed. The main advantage of the proposed method is that it provides an estimation directly at the quantile of interest, thus achieving the parametric rate of convergence. In this study, we investigate the critical role of t…

Fast and Optimal Incremental Parametric Procedure for the Densest Subgraph Problem: An Experimental Study
Dorit S. Hochbaum, Ayleen Irribarra-Cort\'es, Olivier Goldschmidt, Roberto As\'in-Ach\'a
https://arxiv.org/abs/2509.14993

Fast and Optimal Incremental Parametric Procedure for the Densest Subgraph Problem: An Experimental Study
The Densest Subgraph Problem (DSP) is widely used to identify community structures and patterns in networks such as bioinformatics and social networks. While solvable in polynomial time, traditional exact algorithms face computational and scalability limitations, leading to the adoption of faster, but non-optimal, heuristic methods. This work presents the first experimental study of the recently devised Incremental Parametric Cut (IPC) algorithm, which is an exact method for DSP and other "mono…

Reporte de visita m\'edica sobre la aplicaci\'on de braquiterapia de baja tasa con Cs-137 en una paciente con c\'ancer de cuello uterino, estadio IIB
Miguel Angel Mencomo Cede\~no
https://arxiv.org/abs/2509.00306

Reporte de visita médica sobre la aplicación de braquiterapia de baja tasa con Cs-137 en una paciente con cáncer de cuello uterino, estadio IIB
During an academic visit to the National Oncology Institute (ION), the low-dose-rate brachytherapy procedure with Cs-137 was observed in a patient with stage IIB cervical cancer. The experience provided insight into both the clinical preparation of the patient and the dose planning process through imaging studies. Despite certain logistical limitations, strict adherence to safety protocols, disinfection procedures, and radioactive source handling was emphasized. The coordinated participation of…

Can Constructions "SCAN" Compositionality ?
Ganesh Katrapati, Manish Shrivastava
https://arxiv.org/abs/2509.20074 https://arxiv.org/pdf/2509.2007…

Can Constructions "SCAN" Compositionality ?
Sequence to Sequence models struggle at compositionality and systematic generalisation even while they excel at many other tasks. We attribute this limitation to their failure to internalise constructions conventionalised form meaning pairings that license productive recombination. Building on these insights, we introduce an unsupervised procedure for mining pseudo-constructions: variable-slot templates automatically extracted from training data. When applied to the SCAN dataset, our method yie…

Stratification of the half-density quantization of the Jeffrey-Weitsman-Witten invariants
Adrian Chitan
https://arxiv.org/abs/2509.17656 https://arxiv.org/…

Stratification of the half-density quantization of the Jeffrey-Weitsman-Witten invariants
In this paper we review the quantization procedure employed by Jeffrey and Weitsman in their formalization of Witten's three manifold invariants. In so doing, we formalize the stratification of the Lagrangian leaf which corresponds to the flat connections of a bounding surface which extend into the handlebody. The smooth structure of this space motivates a procedure for a stratified quantization: use volumes and corresponding half-densities on the stratified tangent bundle. The pairing is then …

The super learner for time-to-event outcomes: A tutorial
Ruth H. Keogh, Karla Diaz-Ordaz, Nan van Geloven, Jon Michael Gran, Kamaryn T. Tanner
https://arxiv.org/abs/2509.03315 h…

The super learner for time-to-event outcomes: A tutorial
Estimating risks or survival probabilities conditional on individual characteristics based on censored time-to-event data is a commonly faced task. This may be for the purpose of developing a prediction model or may be part of a wider estimation procedure, such as in causal inference. A challenge is that it is impossible to know at the outset which of a set of candidate models will provide the best predictions. The super learner is a powerful approach for finding the best model or combination o…

Random burning of the Euclidean lattice
Guillaume Blanc, Alice Contat
https://arxiv.org/abs/2509.02562 https://arxiv.org/pdf/2509.02562

Random burning of the Euclidean lattice
The burning number of a graph is the minimal number of steps that are needed to burn all of its vertices, with the following burning procedure: at each step, one can choose a point to set on fire, and the fire propagates constantly at unit speed along the edges of the graph. In this paper, we consider two natural random burning procedures in the discrete Euclidean torus $\mathbb{T}_n^d$, in which the points that we set on fire at each step are random variables. Our main result deals with the ca…

The Root Finding Problem Revisited: Beyond the Robbins-Monro procedure
Yue Yu, Moulinath Banerjee, Ya'acov Ritov
https://arxiv.org/abs/2508.17591 https://

The Root Finding Problem Revisited: Beyond the Robbins-Monro procedure
We introduce Sequential Probability Ratio Bisection (SPRB), a novel stochastic approximation algorithm that adapts to the local behavior of the (regression) function of interest around its root. We establish theoretical guarantees for SPRB's asymptotic performance, showing that it achieves the optimal convergence rate and minimal asymptotic variance even when the target function's derivative at the root is small (at most half the step size), a regime where the classical Robbins-Monro procedure …

Packers QB Jordan Love to undergo procedure on left thumb, not expected to miss Week 1 https://www.nfl.com/news/packers-qb-jordan-love-procedure-left-thumb-not-expected-to-miss-week-1

Ik vraag me wel eens af hoeveel mensen de procedure rondom artikel 5 van de NAVO kennen en zich voldoende realiseren dat het geen automatisme is maar unanieme besluitvorming vereist van alle NAVO-leden...
#navo #artikel5

Orchestrating multi-level magic state distillation: a dynamic pipeline architecture
Junshi Wang (University of Cambridge), Prakash Murali (University of Cambridge)
https://arxiv.org/abs/2509.24402

Orchestrating multi-level magic state distillation: a dynamic pipeline architecture
Practical quantum computation requires high-fidelity instruction executions on qubits. Among them, Clifford instructions are relatively easy to perform, while non-Clifford instructions require the use of magic states. This makes magic state distillation a central procedure in fault-tolerant quantum computing. A magic state distillation factory consumes many low-fidelity input magic states and produces fewer, higher-fidelity states. To reach high fidelities, multiple distillation factories are t…

InvBench: Can LLMs Accelerate Program Verification with Invariant Synthesis?
Anjiang Wei, Tarun Suresh, Tianran Sun, Haoze Wu, Ke Wang, Alex Aiken
https://arxiv.org/abs/2509.21629

InvBench: Can LLMs Accelerate Program Verification with Invariant Synthesis?
Program verification relies on loop invariants, yet automatically discovering strong invariants remains a long-standing challenge. We introduce a principled framework for evaluating LLMs on invariant synthesis. Our approach uses a verifier-based decision procedure with a formal soundness guarantee and assesses not only correctness but also the speedup that invariants provide in verification. We evaluate 7 state-of-the-art LLMs, and existing LLM-based verifiers against the traditional solver UAu…

Automatic Model Extraction of the Match Standard in Symmetric--Reciprocal--Match Calibration
Ziad Hatab, Michael Ernst Gadringer, Arash Arsanjani, Wolfgang Boesch
https://arxiv.org/abs/2509.18426

The Pentagon has for months been blocking Ukraine’s use of long-range missiles to strike inside Russia, U.S. officials said,
limiting Kyiv from employing a powerful weapon in its fight against Moscow’s invasion.
A high-level Defense Department approval procedure, which hasn’t been announced, has prevented Ukraine from firing any U.S.-made long-range Army Tactical Missile Systems, deep into Russia

A New Partial State-Feedback IDA-PBC for Two-Dimensional Nonlinear Systems: Application to Power Converters with Experimental Results
Rafael Cisneros, Leyan Fang, Wei He, Romeo Ortega
https://arxiv.org/abs/2510.01425

A New Partial State-Feedback IDA-PBC for Two-Dimensional Nonlinear Systems: Application to Power Converters with Experimental Results
In this paper we propose a variation of the widely popular Interconnection-and-Damping-Assigment Passivity-Based Control (IDA-PBC) based on Poincare's Lemma to design output feedback globally stabilizing controllers for two dimensional systems. The procedure is constructive and, in comparison with the classical IDA-PBC, whose application is often stymied by the need to solve the (infamous) matching partial differential equation (PDE), in this new method the PDE is replaced by an ordinary differ…

Time Tells All: Deanonymization of Blockchain RPC Users with Zero Transaction Fee (Extended Version)
Shan Wang, Ming Yang, Yu Liu, Yue Zhang, Shuaiqing Zhang, Zhen Ling, Jiannong Cao, Xinwen Fu
https://arxiv.org/abs/2508.21440

Time Tells All: Deanonymization of Blockchain RPC Users with Zero Transaction Fee (Extended Version)
Remote Procedure Call (RPC) services have become a primary gateway for users to access public blockchains. While they offer significant convenience, RPC services also introduce critical privacy challenges that remain insufficiently examined. Existing deanonymization attacks either do not apply to blockchain RPC users or incur costs like transaction fees assuming an active network eavesdropper. In this paper, we propose a novel deanonymization attack that can link an IP address of a RPC user to …

Packers QB Love to have left thumb procedure https://www.espn.com/nfl/story/_/id/45955096/packers-jordan-love-thumb-procedure-expected-play-week-1

Adaptive generative moment matching networks for improved learning of dependence structures
Marius Hofert, Gan Yao
https://arxiv.org/abs/2508.21531 https://

Adaptive generative moment matching networks for improved learning of dependence structures
An adaptive bandwidth selection procedure for the mixture kernel in the maximum mean discrepancy (MMD) for fitting generative moment matching networks (GMMNs) is introduced, and its ability to improve the learning of copula random number generators is demonstrated. Based on the relative error of the training loss, the number of kernels is increased during training; additionally, the relative error of the validation loss is used as an early stopping criterion. While training time of such adaptiv…

Quantitative Outcome-Oriented Assessment of Microsurgical Anastomosis
Luyin Hu, Soheil Gholami, George Dindelegan, Torstein R. Meling, Aude Billard
https://arxiv.org/abs/2508.18836

Quantitative Outcome-Oriented Assessment of Microsurgical Anastomosis
Microsurgical anastomosis demands exceptional dexterity and visuospatial skills, underscoring the importance of comprehensive training and precise outcome assessment. Currently, methods such as the outcome-oriented anastomosis lapse index are used to evaluate this procedure. However, they often rely on subjective judgment, which can introduce biases that affect the reliability and efficiency of the assessment of competence. Leveraging three datasets from hospitals with participants at various l…

Resampling-based multi-resolution false discovery exceedance control
Jesse Hemerik
https://arxiv.org/abs/2509.02376 https://arxiv.org/pdf/2509.02376…

Resampling-based multi-resolution false discovery exceedance control
MaxT is a highly popular resampling-based multiple testing procedure, which controls the familywise error rate (FWER) and is powerful under dependence. This paper generalizes maxT to what we term ``multi-resolution'' False Discovery eXceedance (FDX) control. FDX control means ensuring that the FDP -- the proportion of false discoveries among all rejections -- is at most $γ$ with probability at least $1-α$. Here $γ$ and $α$ are prespecified, small values between 0 and 1. If we take $γ=0$, F…

Leveraging LLMs to Improve Experimental Design: A Generative Stratification Approach
George Gui, Seungwoo Kim
https://arxiv.org/abs/2509.25709 https://arxi…

Leveraging LLMs to Improve Experimental Design: A Generative Stratification Approach
Pre-experiment stratification, or blocking, is a well-established technique for designing more efficient experiments and increasing the precision of the experimental estimates. However, when researchers have access to many covariates at the experiment design stage, they often face challenges in effectively selecting or weighting covariates when creating their strata. This paper proposes a Generative Stratification procedure that leverages Large Language Models (LLMs) to synthesize high-dimensio…

Titans activate L'Jarius Sneed from PUP after quad injury, knee clean-up procedure

https://www.cbssports.com/nfl/news/titans-activate-ljarius-sne…

Simultaneous Quantization and Reduction of Constrained Systems
Jianhao M. Yang
https://arxiv.org/abs/2509.22747 https://arxiv.org/pdf/2509.22747

Simultaneous Quantization and Reduction of Constrained Systems
We present a novel framework for quantizing constrained quantum systems in which the processes of quantization and constraint enforcement are performed simultaneously. The approach is based on an extension of the stationary action principle, incorporating an information-theoretic term arising from vacuum fluctuations. Constraints are included directly in the Lagrangian via Lagrange multipliers, allowing the subsequent variational procedure to yield the quantum dynamics without ambiguity regardi…

The US keeps killing people in the international waters near Venezuela, without any procedure, trial or judge. And it is not a warzone. Regardless whether those people are drugs smugglers or not, it is completely illegal and criminal.
But nobody cares.
https://www.axios.com/2025/09/20/us-strik…

U.S. conducts fourth strike against vessel transferring drugs, Trump says
He posted a video of the strike on Truth Social.

Inflationary Slow-Roll Parameters in the Jordan Frame for Cosmological F(R) Gravity Models
Vsevolod R. Ivanov
https://arxiv.org/abs/2508.14250 https://arxi…

Inflationary Slow-Roll Parameters in the Jordan Frame for Cosmological F(R) Gravity Models
$F(R)$ inflationary models are analyzed without the Weyl transformation to the Einstein frame. Sufficient conditions for existence of global inflationary attractors in $F(R)$ models are provided. Following that, the procedure for calculating inflationary observables completely in the original, Jordan, frame is given. The described procedure is used to analyze a new $F(R)$ inflationary model (a one-parameter deformation of the Starobinsky model), which is shown to provide predictions in good agr…

Multiply Robust Inference of Average Treatment Effects by High-dimensional Empirical Likelihood
Xintao Xia, Yumou Qiu
https://arxiv.org/abs/2509.00312 https://

Multiply Robust Inference of Average Treatment Effects by High-dimensional Empirical Likelihood
In this paper, we develop a multiply robust inference procedure of the average treatment effect (ATE) for data with high-dimensional covariates. We consider the case where it is difficult to correctly specify a single parametric model for the propensity scores (PS). For example, the target population is formed from heterogeneous sources with different treatment assignment mechanisms. We propose a novel high-dimensional empirical likelihood weighting method under soft covariate balancing constra…

Eagles OL Landon Dickerson to undergo minor procedure on knee; goal is to be ready for Week 1 https://www.nfl.com/news/eagles-ol-landon-dickerson-to-undergo-minor-procedure-on-knee-goal-is-to-be-ready-for-week-1

$K$-Branching Random Walk with Noisy Selection: Large Population Limits and Phase Transitions
Colin Desmarais, Emmanuel Schertzer, Zs\'ofia Talyig\'as
https://arxiv.org/abs/2509.26254

$K$-Branching Random Walk with Noisy Selection: Large Population Limits and Phase Transitions
We analyze a variant of the Noisy $K$-Branching Random Walk, a population model that evolves according to the following procedure. At each time step, each individual produces a large number of offspring that inherit the fitness of their parents up to independent and identically distributed fluctuations. The next generation consists of a random sample of all the offspring so that the population size remains fixed, where the sampling is made according to a parameterized Gibbs measure of the fitne…

MAD: Manifold Attracted Diffusion
Dennis Elbr\"achter, Giovanni S. Alberti, Matteo Santacesaria
https://arxiv.org/abs/2509.24710 https://arxiv.org/pdf…

MAD: Manifold Attracted Diffusion
Score-based diffusion models are a highly effective method for generating samples from a distribution of images. We consider scenarios where the training data comes from a noisy version of the target distribution, and present an efficiently implementable modification of the inference procedure to generate noiseless samples. Our approach is motivated by the manifold hypothesis, according to which meaningful data is concentrated around some low-dimensional manifold of a high-dimensional ambient s…

Bringing Closure to False Discovery Rate Control: A General Principle for Multiple Testing
Ziyu Xu, Aldo Solari, Lasse Fischer, Rianne de Heide, Aaditya Ramdas, Jelle Goeman
https://arxiv.org/abs/2509.02517

Bringing Closure to False Discovery Rate Control: A General Principle for Multiple Testing
We present a novel necessary and sufficient principle for multiple testing methods controlling an expected loss. This principle asserts that every such multiple testing method is a special case of a general closed testing procedure based on e-values. It generalizes the Closure Principle, known to underlie all methods controlling familywise error and tail probabilities of false discovery proportions, to a large class of error rates -- in particular to the false discovery rate (FDR). By writing e…

YOLO-LAN: Precise Polyp Detection via Optimized Loss, Augmentations and Negatives
Siddharth Gupta, Jitin Singla
https://arxiv.org/abs/2509.19166 https://ar…

State-to-Hamiltonian conversion with a few copies
Kaito Wada, Jumpei Kato, Hiroyuki Harada, Naoki Yamamoto
https://arxiv.org/abs/2509.14791 https://arxiv.o…

State-to-Hamiltonian conversion with a few copies
Density matrix exponentiation (DME) is a general procedure that converts an unknown quantum state into the Hamiltonian evolution. This enables state-dependent operations and can reveal nontrivial properties of the state, among other applications, without full tomography. However, it has been proven that for any physical process, the DME requires $Θ(1/\varepsilon)$ state copies in error $\varepsilon$. In this work, we go beyond the lower bound and propose a procedure called the virtual DME that…

Semiparametric model averaging for high-dimensional quantile regression with nonignorable nonresponse
Wei Xiong, Dianliang Deng, Dehui Wang
https://arxiv.org/abs/2509.00464 http…

Semiparametric model averaging for high-dimensional quantile regression with nonignorable nonresponse
Model averaging has demonstrated superior performance for ensemble forecasting in high-dimensional framework, its extension to incomplete datasets remains a critical but underexplored challenge. Moreover, identifying the parsimonious model through averaging procedure in quantile regression demands urgent methodological innovation. In this paper, we propose a novel model averaging method for high-dimensional quantile regression with nonignorable missingness. The idea is to relax the parametric c…

Statistical Inference for Gradient Boosting Regression
Haimo Fang, Kevin Tan, Giles Hooker
https://arxiv.org/abs/2509.23127 https://arxiv.org/pdf/2509.2312…

Statistical Inference for Gradient Boosting Regression
Gradient boosting is widely popular due to its flexibility and predictive accuracy. However, statistical inference and uncertainty quantification for gradient boosting remain challenging and under-explored. We propose a unified framework for statistical inference in gradient boosting regression. Our framework integrates dropout or parallel training with a recently proposed regularization procedure that allows for a central limit theorem (CLT) for boosting. With these enhancements, we surprising…

Packers QB Jordan Love will have procedure on left thumb ligament, hopes to return to practice next week

https://www.cbssports.com/nfl/news/packers

Optimal smoothing parameter in Eilers-Wittaker smoother
Roberto Bernal-Arencibia, Karel Garcia Medina, Ernesto Estevez-Rams, Beatriz Aragon-Fernandez
https://arxiv.org/abs/2510.01798

Optimal smoothing parameter in Eilers-Wittaker smoother
The Eilers-Whittaker method for data smoothing effectiveness depends on the choice of the regularisation parameter, and automatic selection is a necessity for large datasets. Common methods, such as leave-one-out cross-validation, can perform poorly when serially correlated noise is present. We propose a novel procedure for selecting the control parameter based on the spectral entropy of the residuals. We define an S-curve from the Euclidean distance between points in a plot of the spectral ent…

Synthesis and SOS-based Stability Verification of a Neural-Network-Based Controller for a Two-wheeled Inverted Pendulum
Alvaro Detailleur, Dalim Wahby, Guillaume Ducard, Christopher Onder
https://arxiv.org/abs/2508.15616

Synthesis and SOS-based Stability Verification of a Neural-Network-Based Controller for a Two-wheeled Inverted Pendulum
This work newly establishes the feasibility and practical value of a sum of squares (SOS)-based stability verification procedure for applied control problems utilizing neural-network-based controllers (NNCs). It successfully verifies closed-loop stability properties of a NNC synthesized using a generalizable procedure to imitate a robust, tube-based model predictive controller (MPC) for a two-wheeled inverted pendulum demonstrator system. This is achieved by first developing a state estimator a…

An adaptive procedure for detecting replicated signals with $k$-family-wise error rate control
Ninh Tran
https://arxiv.org/abs/2508.15363 https://arxiv.org…

An adaptive procedure for detecting replicated signals with $k$-family-wise error rate control
Partial conjunction (PC) hypothesis testing is widely used to assess the replicability of scientific findings across multiple comparable studies. In high-throughput meta-analyses, testing a large number of PC hypotheses with k-family-wise error rate (k-FWER) control often suffers from low statistical power due to the multiplicity burden. The state-of-the-art AdaFilter-Bon procedure by Wang et al. (2022, Ann. Stat., 50(4), 1890-1909) alleviates this problem by filtering out hypotheses unlikely t…

Sparse minimum Redundancy Maximum Relevance for feature selection
Peter Naylor, Benjamin Poignard, H\'ector Climente-Gonz\'alez, Makoto Yamada
https://arxiv.org/abs/2508.18901

Sparse minimum Redundancy Maximum Relevance for feature selection
We propose a feature screening method that integrates both feature-feature and feature-target relationships. Inactive features are identified via a penalized minimum Redundancy Maximum Relevance (mRMR) procedure, which is the continuous version of the classic mRMR penalized by a non-convex regularizer, and where the parameters estimated as zero coefficients represent the set of inactive features. We establish the conditions under which zero coefficients are correctly identified to guarantee acc…

Calibrated Counterfactual Conformal Fairness ($C^3F$): Post-hoc, Shift-Aware Coverage Parity via Conformal Prediction and Counterfactual Regularization
Faruk Alpay, Taylan Alpay
https://arxiv.org/abs/2509.25295

Calibrated Counterfactual Conformal Fairness ($C^3F$): Post-hoc, Shift-Aware Coverage Parity via Conformal Prediction and Counterfactual Regularization
We present Calibrated Counterfactual Conformal Fairness ($C^3F$), a post-hoc procedure that targets group-conditional coverage parity under covariate shift. $C^3F$ combines importance-weighted conformal calibration with a counterfactual regularizer based on path-specific effects in a structural causal model. The method estimates group-specific nonconformity quantiles using likelihood-ratio weights so that coverage degrades gracefully with the second moment of the weights. We derive finite-sampl…

Sources: Eagles eye Dickerson meniscus injury https://www.espn.com/nfl/story/_/id/45945721/sources-eagles-dickerson-thought-meniscus-injury

Federated Learning of Quantile Inference under Local Differential Privacy
Leheng Cai, Qirui Hu, Shuyuan Wu
https://arxiv.org/abs/2509.21800 https://arxiv.o…

Federated Learning of Quantile Inference under Local Differential Privacy
In this paper, we investigate federated learning for quantile inference under local differential privacy (LDP). We propose an estimator based on local stochastic gradient descent (SGD), whose local gradients are perturbed via a randomized mechanism with global parameters, making the procedure tolerant of communication and storage constraints without compromising statistical efficiency. Although the quantile loss and its corresponding gradient do not satisfy standard smoothness conditions typica…

Tail-robust estimation of factor-adjusted vector autoregressive models for high-dimensional time series
Dylan Dijk, Haeran Cho
https://arxiv.org/abs/2509.22235 https://

Tail-robust estimation of factor-adjusted vector autoregressive models for high-dimensional time series
We study the problem of modelling high-dimensional, heavy-tailed time series data via a factor-adjusted vector autoregressive (VAR) model, which simultaneously accounts for pervasive co-movements of the variables by a handful of factors, as well as their remaining interconnectedness using a sparse VAR model. To accommodate heavy tails, we adopt an element-wise truncation step followed by a two-stage estimation procedure for estimating the latent factors and the VAR parameter matrices. Assuming …