Tootfinder

Bolts' Harbaugh had cardiac ablation, hip surgery https://www.espn.com/nfl/story/_/id/45488352/chargers-coach-jim-harbaugh-gives-update-offseason-medical-procedures

EU's Frontex has published a children's book for children who are about to be deported
😲
https://op.europa.eu/en/publication-detail/-/publication/6eea0e99-e464-11ef-be2a-01aa75ed71a1
Official PDFs availabl…

Toolbox for children in return - Publications Office of the EU
Addressing the return of unaccompanied minors or children within families is a delicate matter that demands a humane approach. This approach must not only respect fundamental rights but also prioritise the child's best interests. Additionally, clear and comprehensive information about the return procedures is essential for those involved, enabling them to prepare as effectively as possible. One of the primary objectives of Frontex is to assist MS throughout all stages of the return procedures. …

Data warehouses, lakes, lakehouses, and more – our choices significantly affect operational costs and development speed. Join Lars Albertsson at Berlin Buzzwords to explore how different data processing paradigms impact deployment, failure handling, and data quality. Learn strategies to minimise costs and latency, bridge between paradigms, and enhance development iteration and operational efficiency.
Learn more:

From IOCs to Group Profiles: On the Specificity of Threat Group Behaviors in CTI Knowledge Bases
Aakanksha Saha, Martina Lindorfer, Juan Caballero
https://arxiv.org/abs/2506.10645

From IOCs to Group Profiles: On the Specificity of Threat Group Behaviors in CTI Knowledge Bases
Indicators of Compromise (IOCs) such as IP addresses, file hashes, and domain names are commonly used for threat detection and attribution. However, IOCs tend to be short-lived as they are easy to change. As a result, the cybersecurity community is shifting focus towards more persistent behavioral profiles, such as the Tactics, Techniques, and Procedures (TTPs) and the software used by a threat group. However, the distinctiveness and completeness of such behavioral profiles remain largely unexp…

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Bao Zhang, Zihan Li, Zhenglei Liu, Huanchen Wang, Yuxin Ma
https://arxiv.org/abs/2506.10762

Integrating Large Language Models into Text Animation: An Intelligent Editing System with Inline and Chat Interaction
Text animation, a foundational element in video creation, enables efficient and cost-effective communication, thriving in advertisements, journalism, and social media. However, traditional animation workflows present significant usability barriers for non-professionals, with intricate operational procedures severely hindering creative productivity. To address this, we propose a Large Language Model (LLM)-aided text animation editing system that enables real-time intent tracking and flexible edi…

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning
Jiayu Li, Masood Mortazavi, Ning Yan, Yihong Ma, Reza Zafarani
https://arxiv.org/abs/2506.08029

Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning
The goal of inverse design in distributed circuits is to generate near-optimal designs that meet a desirable transfer function specification. Existing design exploration methods use some combination of strategies involving artificial grids, differentiable evaluation procedures, and specific template topologies. However, real-world design practices often require non-differentiable evaluation procedures, varying topologies, and near-continuous placement spaces. In this paper, we propose DCIDA, a …

GP leaders have halted progress on a predictive AI model based citing concern about whether the correct procedures were followed. The pause is likely to frustrate those advocating for greater use of AI within healthcare.
https://www.computing.co.uk/news/2025/ai/gps-f…

GPs force NHS England to hit pause on a ‘ground-breaking’ AI project
GP leaders have halted progress on a predictive AI model based citing concern about whether the correct procedures were followed. The pause is likely to ...

I am still alive, but it's been a hectic several weeks and I've not been both idle and online together.
It started with joy as my eldest graduated from high school -- one of several valedictorians. We are, of course, immensely proud. Parties and celebrations were our constant companions.
Then, off to Indianapolis, to be with my dad and stepmom, providing aid and care while he underwent two successful surgical procedures. The recovery has not been as linear as I'd like…

I think it is time to start organizing Peoples' Courts to try FFOTUS and his maga-klan.
Right now it is sufficient to define the general shape of the courts, their jurisdiction, the outline of procedures, and to enunciate the "natural law" standards to which the accused will be measured.
I generally hate the concept of "natural law", but in this case it is apt because that's what the maga-heads seem to like (see abominations such many cases from SCOTUS…

Token Perturbation Guidance for Diffusion Models
Javad Rajabi, Soroush Mehraban, Seyedmorteza Sadat, Babak Taati
https://arxiv.org/abs/2506.10036 https://

Token Perturbation Guidance for Diffusion Models
Classifier-free guidance (CFG) has become an essential component of modern diffusion models to enhance both generation quality and alignment with input conditions. However, CFG requires specific training procedures and is limited to conditional generation. To address these limitations, we propose Token Perturbation Guidance (TPG), a novel method that applies perturbation matrices directly to intermediate token representations within the diffusion network. TPG employs a norm-preserving shuffling…

Next stop on our NLP timeline (as part of the #ISE2025 lecture) was Terry Winograd's SHRDLU, an early natural language understanding system developed in 1968-70 that could manipulate blocks in a virtual world.
Winograd, T. Procedures as a Representation for Data in a Computer Program for Understanding Natural Language. MIT AI Technical Report 235.

Machine learning for in-situ composition mapping in a self-driving magnetron sputtering system
Sanna Jarl, Jens Sj\"olund, Robert J. W. Frost, Anders Holst, Jonathan J. S. Scragg
https://arxiv.org/abs/2506.05999

Machine learning for in-situ composition mapping in a self-driving magnetron sputtering system
Self-driving labs (SDLs), employing automation and machine learning (ML) to accelerate experimental procedures, have enormous potential in the discovery of new materials. However, in thin film science, SDLs are mainly restricted to solution-based synthetic methods which are easier to automate but cannot access the broad chemical space of inorganic materials. This work presents an SDL based on magnetron co-sputtering. We are using combinatorial frameworks, obtaining accurate composition maps on …

BESS Participation Planning for Provision of Grid Services in Energy and Regulation Markets
Zeenat Hameed, Chresten Traeholt
https://arxiv.org/abs/2506.08472

BESS Participation Planning for Provision of Grid Services in Energy and Regulation Markets
This paper presents a stochastic optimization model for planning the participation of battery energy storage systems (BESSs) in energy and regulation markets. The proposed model quantifies and compares the business value of single and multi-market BESS services by accounting for their bid submission and acceptance procedures, pricing mechanisms and revenue streams, and penalty payments and degradation costs. By modelling the price uncertainties using market price scenarios (MPSs) and considerin…

AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Nanda Rani, Sandeep Kumar Shukla
https://arxiv.org/abs/2506.10175

AURA: A Multi-Agent Intelligence Framework for Knowledge-Enhanced Cyber Threat Attribution
Effective attribution of Advanced Persistent Threats (APTs) increasingly hinges on the ability to correlate behavioral patterns and reason over complex, varied threat intelligence artifacts. We present AURA (Attribution Using Retrieval-Augmented Agents), a multi-agent, knowledge-enhanced framework for automated and interpretable APT attribution. AURA ingests diverse threat data including Tactics, Techniques, and Procedures (TTPs), Indicators of Compromise (IoCs), malware details, adversarial to…

MD-ViSCo: A Unified Model for Multi-Directional Vital Sign Waveform Conversion
Franck Meyer, Kyunghoon Hur, Edward Choi
https://arxiv.org/abs/2506.08357 ht…

MD-ViSCo: A Unified Model for Multi-Directional Vital Sign Waveform Conversion
Despite the remarkable progress of deep-learning methods generating a target vital sign waveform from a source vital sign waveform, most existing models are designed exclusively for a specific source-to-target pair. This requires distinct model architectures, optimization procedures, and pre-processing pipelines, resulting in multiple models that hinder usability in clinical settings. To address this limitation, we propose the Multi-Directional Vital-Sign Converter (MD-ViSCo), a unified framewo…

DOGE vowed to make government more ‘efficient’ — but it’s doing the opposite - The Washington Post #USA #Trump

DOGE vowed to make government more ‘efficient’ — but it’s doing the opposite
New procedures and requirements — some implemented in the name of improving operations — are slowing down federal agencies.

Pairwise similarity method for majority domination problem
N. I. Shushko, D. V. Lemtyuzhnikova
https://arxiv.org/abs/2506.08886 https://

Pairwise similarity method for majority domination problem
The paper considers the problem of finding the number of dominant voters in two-level voting procedures. At the first stage, voting is conducted among local groups of voters, and at the second stage, the results are aggregated to form a final decision. The goal is to determine the minimum proportion of voters supporting a proposal for it to be accepted. The paper uses the method of pairwise comparisons to analyze the structure of the problem and develop heuristic algorithms with guaranteed accu…

Scalable Language Agnostic Taint Tracking using Explicit Data Dependencies
Sedick David Baker Effendi, Xavier Pinho, Andrei Michael Dreyer, Fabian Yamaguchi
https://arxiv.org/abs/2506.06247

Scalable Language Agnostic Taint Tracking using Explicit Data Dependencies
Taint analysis using explicit whole-program data-dependence graphs is powerful for vulnerability discovery but faces two major challenges. First, accurately modeling taint propagation through calls to external library procedures requires extensive manual annotations, which becomes impractical for large ecosystems. Second, the sheer size of whole-program graph representations leads to serious scalability and performance issues, particularly when quick analysis is needed in continuous development…

Slovakia: Attacks on the media, judiciary and NGOs
Members of the European Parliament condemned the harsh rhetoric used by Slovak officials against judges, the media and NGOs, warning that it fosters aggression against journalists and restricts access to information.
Wilmès expressed concern over the recent restructuring of the public broadcaster STVR and the use of accelerated legislative procedures.
Concerns were also voiced about the dismantling of the anti-corruption a…

2-Segal sets and pseudomonoids in the bicategory of spans
Sophia E Marx, Rajan Amit Mehta
https://arxiv.org/abs/2505.22832 https://ar…

2-Segal sets and pseudomonoids in the bicategory of spans
In this survey article, we give an introduction to the notion of a 2-Segal set and prove that 2-Segal sets are equivalent to pseudomonoids in the bicategory of spans. The proof utilizes graphical techniques for 2-Segal sets and spans that should be useful in more general settings. There are procedures for obtaining an associative algebra from a 2-Segal set (satisfying finiteness conditions). We describe these procedures and give several examples of algebras arising from 2-Segal sets. Wherev…

Automatic Treatment Planning using Reinforcement Learning for High-dose-rate Prostate Brachytherapy
Tonghe Wang, Yining Feng, Xiaofeng Yang
https://arxiv.org/abs/2506.09805

Automatic Treatment Planning using Reinforcement Learning for High-dose-rate Prostate Brachytherapy
Purpose: In high-dose-rate (HDR) prostate brachytherapy procedures, the pattern of needle placement solely relies on physician experience. We investigated the feasibility of using reinforcement learning (RL) to provide needle positions and dwell times based on patient anatomy during pre-planning stage. This approach would reduce procedure time and ensure consistent plan quality. Materials and Methods: We train a RL agent to adjust the position of one selected needle and all the dwell times on i…

This https://arxiv.org/abs/2505.22990 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

MenTeR: A fully-automated Multi-agenT workflow for end-to-end RF/Analog Circuits Netlist Design
RF/Analog design is essential for bridging digital technologies with real-world signals, ensuring the functionality and reliability of a wide range of electronic systems. However, analog design procedures are often intricate, time-consuming and reliant on expert intuition, and hinder the time and cost efficiency of circuit development. To overcome the limitations of the manual circuit design, we introduce MenTeR - a multiagent workflow integrated into an end-to-end analog design framework. By e…

PVV-minister wilde op ‘Trump-achtige’ wijze weer overal naar 130 kilometer per uur | Politiek | AD.nl
https://www.ad.nl/article/~a1e4e24b/
Ahh ... Van die 1e, 2e en 3e prioriteit om overal weer (eventjes) 130 km/u te mogen rijden is ook al vrijwel niets terecht gekomen... 😂

Inference on the value of linear programs
Leonard Goff, Eric Mbakop
https://arxiv.org/abs/2506.06776 https://arxiv.org/pdf/2506.06776…

Inference on the value of linear programs
This paper studies inference on the value of linear programs (LPs) when both the objective function and constraints are possibly unknown and must be estimated from data. We show that many inference problems in partially identified models can be reformulated in this way. Building on Shapiro (1991) and Fang and Santos (2019), we develop a pointwise valid inference procedure for the value of LPs. We modify this pointwise inference procedure to construct one-sided inference procedures that are unif…

This https://arxiv.org/abs/2502.03956 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLO_…

POPACheck: A Model Checker for Probabilistic Pushdown Automata
We present POPACheck, the first model checking tool for probabilistic Pushdown Automata (pPDA) supporting temporal logic specifications. POPACheck provides a user-friendly probabilistic modeling language with recursion that automatically translates into Probabilistic Operator Precedence Automata (pOPA). pOPA are a class of pPDA that can express all the behaviors of probabilistic programs: sampling, conditioning, recursive procedures, and nested inference queries. On pOPA, POPACheck can solve re…

A simple GUI-based screencast demo of the @… AI Layer (OPAL), showing what’s now possible via MCP A2A—namely, composing and orchestrating agentic workflows through loosely coupled software.
How?
An Agent Host routes tasks to Agents via A2A. Agents then invoke MCP-accessible tools (functions, procedures, APIs) described using JSON/YAML and exposed …

Surgical Foundation Model Leveraging Compression and Entropy Maximization for Image-Guided Surgical Assistance
Lianhao Yin, Ozanan Meireles, Guy Rosman, Daniela Rus
https://arxiv.org/abs/2506.01980

Surgical Foundation Model Leveraging Compression and Entropy Maximization for Image-Guided Surgical Assistance
Real-time video understanding is critical to guide procedures in minimally invasive surgery (MIS). However, supervised learning approaches require large, annotated datasets that are scarce due to annotation efforts that are prohibitive, e.g., in medical fields. Although self-supervision methods can address such limitations, current self-supervised methods often fail to capture structural and physical information in a form that generalizes across tasks. We propose Compress-to-Explore (C2E), a no…

This https://arxiv.org/abs/2404.03152 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Orthogonal calibration via posterior projections with applications to the Schwarzschild model
The orbital superposition method originally developed by Schwarzschild (1979) is used to study the dynamics of growth of a black hole and its host galaxy, and has uncovered new relationships between the galaxy's global characteristics. Scientists are specifically interested in finding optimal parameter choices for this model that best match physical measurements along with quantifying the uncertainty of such procedures. This renders a statistical calibration problem with multivariate outcomes. …

This https://arxiv.org/abs/2504.10484 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hept…

Generalized Symmetries of Non-SUSY and Discrete Torsion String Backgrounds
String / M-theory backgrounds with degrees of freedom at a localized singularity provide a general template for generating strongly correlated systems decoupled from lower-dimensional gravity. There are by now several complementary procedures for extracting the associated generalized symmetry data from orbifolds of the form $\mathbb{R}^6 / Γ$, including methods based on the boundary topology of the asymptotic geometry, as well as the adjacency matrix for fermionic degrees of freedom in the qui…

Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
Timothy B Mahoney, JingYang Liu, Huakun Xin, David B Grayden, Sam E John
https://arxiv.org/abs/2506.03452

Minimally Invasive Brain Computer Interfaces: Evaluating the Impact of Tissue Layers on Signal Quality of Sub-Scalp EEG
Individuals with severe physical disabilities often experience diminished quality of life stemming from limited ability to engage with their surroundings. Brain-Computer Interface (BCI) technology aims to bridge this gap by enabling direct technology interaction. However, current BCI systems require invasive procedures, such as craniotomy or implantation of electrodes through blood vessels, posing significant risks to patients. Sub-scalp electroencephalography (EEG) offers a lower risk alternat…

This https://arxiv.org/abs/2505.00616 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Catastrophic Liability: Managing Systemic Risks in Frontier AI Development
As artificial intelligence systems grow more capable and autonomous, frontier AI development poses potential systemic risks that could affect society at a massive scale. Current practices at many AI labs developing these systems lack sufficient transparency around safety measures, testing procedures, and governance structures. This opacity makes it challenging to verify safety claims or establish appropriate liability when harm occurs. Drawing on liability frameworks from nuclear energy, aviati…

Accurate analysis of the pitch pulse-based magnitude/phase structure of natural vowels and assessment of three lightweight time/frequency voicing restoration methods
An\'ibal J. S. Ferreira, Luis M. T. Jesus, Laurentino M. M. Leal, Jorge E. F. Spratley
https://arxiv.org/abs/2506.06675

Accurate analysis of the pitch pulse-based magnitude/phase structure of natural vowels and assessment of three lightweight time/frequency voicing restoration methods
Whispered speech is produced when the vocal folds are not used, either intentionally, or due to a temporary or permanent voice condition. The essential difference between natural speech and whispered speech is that periodic signal components that exist in certain regions of the former, called voiced regions, as a consequence of the vibration of the vocal folds, are missing in the latter. The restoration of natural speech from whispered speech requires delicate signal processing procedures that …

Optimization of the multiple sampling and signal extraction in non-destructive exposures
B. Kubik, R. Barbier, A. Castera, E. Chabanat, S. Ferriol, G. Smadja
https://arxiv.org/abs/2506.04904

Optimization of the multiple sampling and signal extraction in non-destructive exposures
We derive the full covariance matrix formulae are derived for proper treatment of correlations in signal fitting procedures, extending the results from previous publications. The straight line fits performed with these matrices demonstrate that a significantly higher signal to noise is obtained when the fluence exceeds 1 e/sec/pix in particular in long (several hundreds of seconds) spectroscopic exposures. The improvement arising from the covariance matrix is particularly strong for the initial…

At the edge of Donsker's Theorem: Asymptotics of multiscale scan statistics
Johann K\"ohne, Fabian Mies
https://arxiv.org/abs/2506.05112 https://

At the edge of Donsker's Theorem: Asymptotics of multiscale scan statistics
For nonparametric inference about a function, multiscale testing procedures resolve the need for bandwidth selection and achieve asymptotically optimal detection performance against a broad range of alternatives. However, critical values strongly depend on the noise distribution, and we argue that existing methods are either statistically infeasible, or asymptotically sub-optimal. To address this methodological challenge, we show how to develop a feasible multiscale test via weak convergence ar…

Government, brought to you by the people who paid people to take their tests in college....
"Nobody has ever accused RFK Jr. of academic rigor,” said Marion Nestle, a professor emerita of nutrition, food studies and public health at New York University. "The speed (of the MAHA report) suggests that it could not have been vetted carefully and must have been whisked through standard clearance procedures. The citation problem suggests a reliance on AI."

This https://arxiv.org/abs/2506.05164 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

Towards the target and not beyond: 2d vs 3d visual aids in mr-based neurosurgical simulation
Neurosurgery increasingly uses Mixed Reality (MR) technologies for intraoperative assistance. The greatest challenge in this area is mentally reconstructing complex 3D anatomical structures from 2D slices with millimetric precision, which is required in procedures like External Ventricular Drain (EVD) placement. MR technologies have shown great potential in improving surgical performance, however, their limited availability in clinical settings underscores the need for training systems that fos…

Beyond the Desktop: XR-Driven Segmentation with Meta Quest 3 and MX Ink
Lisle Faray de Paiva, Gijs Luijten, Ana Sofia Ferreira Santos, Moon Kim, Behrus Puladi, Jens Kleesiek, Jan Egger
https://arxiv.org/abs/2506.04858

Beyond the Desktop: XR-Driven Segmentation with Meta Quest 3 and MX Ink
Medical imaging segmentation is essential in clinical settings for diagnosing diseases, planning surgeries, and other procedures. However, manual annotation is a cumbersome and effortful task. To mitigate these aspects, this study implements and evaluates the usability and clinical applicability of an extended reality (XR)-based segmentation tool for anatomical CT scans, using the Meta Quest 3 headset and Logitech MX Ink stylus. We develop an immersive interface enabling real-time interaction w…

Towards model-based design of causal manipulations of brain circuits with high spatiotemporal precision
Anandita De, Roozbeh Kiani, Luca Mazzucato
https://arxiv.org/abs/2505.24790

Towards model-based design of causal manipulations of brain circuits with high spatiotemporal precision
Recent advancements in neurotechnology enable precise spatiotemporal patterns of microstimulations with single-cell resolution. The choice of perturbation sites must satisfy two key criteria: efficacy in evoking significant responses and selectivity for the desired target effects. This choice is currently based on laborious trial-and-error procedures, unfeasible for sequences of multi-site stimulations. Efficient methods to design complex perturbation patterns are urgently needed. Can we design…

This https://arxiv.org/abs/2505.24785 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

EXP-Bench: Can AI Conduct AI Research Experiments?
Automating AI research holds immense potential for accelerating scientific progress, yet current AI agents struggle with the complexities of rigorous, end-to-end experimentation. We introduce EXP-Bench, a novel benchmark designed to systematically evaluate AI agents on complete research experiments sourced from influential AI publications. Given a research question and incomplete starter code, EXP-Bench challenges AI agents to formulate hypotheses, design and implement experimental procedures, …

This https://arxiv.org/abs/2408.09955 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMA_…

MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs
LLM-based multi-agent systems (MAS) have shown promise in tackling complex tasks. However, existing solutions often suffer from limited agent coordination and heavy reliance on predefined Standard Operating Procedures (SOPs), which demand extensive human input. To address these limitations, we propose MegaAgent, a large-scale autonomous LLM-based multi-agent system. MegaAgent generates agents based on task complexity and enables dynamic task decomposition, parallel execution, efficient communic…

SurGSplat: Progressive Geometry-Constrained Gaussian Splatting for Surgical Scene Reconstruction
Yuchao Zheng, Jianing Zhang, Guochen Ning, Hongen Liao
https://arxiv.org/abs/2506.05935

SurGSplat: Progressive Geometry-Constrained Gaussian Splatting for Surgical Scene Reconstruction
Intraoperative navigation relies heavily on precise 3D reconstruction to ensure accuracy and safety during surgical procedures. However, endoscopic scenarios present unique challenges, including sparse features and inconsistent lighting, which render many existing Structure-from-Motion (SfM)-based methods inadequate and prone to reconstruction failure. To mitigate these constraints, we propose SurGSplat, a novel paradigm designed to progressively refine 3D Gaussian Splatting (3DGS) through the …

Toward Effective AI Governance: A Review of Principles
Danilo Ribeiro, Thayssa Rocha, Gustavo Pinto, Bruno Cartaxo, Marcelo Amaral, Nicole Davila, Ana Camargo
https://arxiv.org/abs/2505.23417

Toward Effective AI Governance: A Review of Principles
Artificial Intelligence (AI) governance is the practice of establishing frameworks, policies, and procedures to ensure the responsible, ethical, and safe development and deployment of AI systems. Although AI governance is a core pillar of Responsible AI, current literature still lacks synthesis across such governance frameworks and practices. Objective: To identify which frameworks, principles, mechanisms, and stakeholder roles are emphasized in secondary literature on AI governance. Method: We…

This https://arxiv.org/abs/2502.13128 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

SongGen: A Single Stage Auto-regressive Transformer for Text-to-Song Generation
Text-to-song generation, the task of creating vocals and accompaniment from textual inputs, poses significant challenges due to domain complexity and data scarcity. Existing approaches often employ multi-stage generation procedures, leading to cumbersome training and inference pipelines, as well as suboptimal overall generation quality due to error accumulation across stages. In this paper, we propose SongGen, a fully open-source, single-stage auto-regressive transformer designed for controllab…

This https://arxiv.org/abs/2505.22598 has been replaced.
initial toot: https://mastoxiv.page/@arX…

On the performance of machine-learning assisted Monte Carlo in sampling from simple statistical physics models
Recent years have seen a rise in the application of machine learning techniques to aid the simulation of hard-to-sample systems that cannot be studied using traditional methods. Despite the introduction of many different architectures and procedures, a wide theoretical understanding is still lacking, with the risk of suboptimal implementations. As a first step to address this gap, we provide here a complete analytic study of the widely-used Sequential Tempering procedure applied to a shallow MA…

This https://arxiv.org/abs/2505.08408 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A three-term Polak-Ribière-Polyak conjugate gradient method for vector optimization
A three-term Polak-Ribière-Polyak conjugate gradient method is first proposed in this paper for solving vector optimization problems. This method can autonomously generate descent directions independent of line search procedures, while retaining the conjugate property. The global convergence of the proposed scheme is established by the generalized Wolfe line search procedure without self-adjusting strategies, regular restarts and convexity assumptions. Finally, numerical experiments illustrati…

This https://arxiv.org/abs/2212.05260 has been replaced.
link: https://scholar.google.com/scholar?q=a

Examining marginal properness in the external validation of survival models with squared and logarithmic losses
Scoring rules promote rational and honest decision-making, which is important for model evaluation and becoming increasingly important for automated procedures such as `AutoML'. In this paper we survey common squared and logarithmic scoring rules for survival analysis, with a focus on their theoretical and empirical properness. We introduce a marginal definition of properness and show that both the Integrated Survival Brier Score (ISBS) and the Right-Censored Log-Likelihood (RCLL) are theoretic…

This https://arxiv.org/abs/2502.06830 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Prediction
Accurate and reliable probabilistic prediction of intraday electricity prices is essential to manage market uncertainties and support robust trading strategies. However, current methods rely heavily on domain feature extraction and fail to capture the dynamics between buy and sell orders, limiting the ability to form rich representations of the orderbook. Furthermore, these methods often require training separate models for different quantiles and introduce additional procedures-such as post-ho…

This https://arxiv.org/abs/2505.08408 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A three-term Polak-Ribière-Polyak conjugate gradient method for vector optimization
A three-term Polak-Ribière-Polyak conjugate gradient method is first proposed in this paper for solving vector optimization problems. This method can autonomously generate descent directions independent of line search procedures, while retaining the conjugate property. The global convergence of the proposed scheme is established by the generalized Wolfe line search procedure without self-adjusting strategies, regular restarts and convexity assumptions. Finally, numerical experiments illustrati…

This https://arxiv.org/abs/2402.18306 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Calibration requirement for Epoch of Reionization 21-cm signal observation -- III. Bias and variance in uGMRT ELAIS-N1 field power spectrum
Power spectrum of \HI 21-cm radiation is one of the promising probes to study large scale structure of the universe and understand galaxy formation and evolution. The presence of foregrounds, that are orders of magnitude larger in the same frequency range of the redshifted 21-cm signal has been one of the largest observational challenges. The foreground contamination also hinders the calibration procedures and introduces residual calibration errors in the interferometric data. It has been shown…

This https://arxiv.org/abs/2311.06891 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Design-based Estimation Theory for Complex Experiments
This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units. We develop a design-based estimation theory for arbitrary experimental designs. Our theory facilitates the analysis of many design-estimator pairs that researchers commonly employ in practice and provide procedures to consistently estimate asymptotic variance bounds. We propose new classes of estimators with favorable asymptotic p…

Towards the target and not beyond: 2d vs 3d visual aids in mr-based neurosurgical simulation
Pasquale Cascarano, Andrea Loretti, Matteo Martinoni, Luca Zanuttini, Alessio Di Pasquale, Gustavo Marfia
https://arxiv.org/abs/2506.05164

Towards the target and not beyond: 2d vs 3d visual aids in mr-based neurosurgical simulation
Neurosurgery increasingly uses Mixed Reality (MR) technologies for intraoperative assistance. The greatest challenge in this area is mentally reconstructing complex 3D anatomical structures from 2D slices with millimetric precision, which is required in procedures like External Ventricular Drain (EVD) placement. MR technologies have shown great potential in improving surgical performance, however, their limited availability in clinical settings underscores the need for training systems that fos…

Asymptotic analysis of high-dimensional uniformity tests under heavy-tailed alternatives
Tiefeng Jiang, Tuan Pham
https://arxiv.org/abs/2506.00393 https://…

Asymptotic analysis of high-dimensional uniformity tests under heavy-tailed alternatives
We study the high-dimensional uniformity testing problem, which involves testing whether the underlying distribution is the uniform distribution, given $n$ data points on the $p$-dimensional unit hypersphere. While this problem has been extensively studied in scenarios with fixed $p$, only three testing procedures are known in high-dimensional settings: the Rayleigh test \cite{Cutting-P-V}, the Bingham test \cite{Cutting-P-V2}, and the packing test \cite{Jiang13}. Most existing research focuses…

The Use of Alendronate to Enhance Transcranial Transmission of Focused Ultrasound for Successful Ablations in Brain
G. Sakharova, A. Krokhmal, R. Galimova, A. Khatmullina, D. Nabiullina, I. Buzaev, D. Avzaletdinova, D. Chupova, V. Khokhlova
https://arxiv.org/abs/2505.24349

The Use of Alendronate to Enhance Transcranial Transmission of Focused Ultrasound for Successful Ablations in Brain
Objective: The aim of this study was to evaluate the efficacy of alendronate therapy in improving bone density distribution in skull bones and corresponding ultrasound permeability in patients who had previously experienced unsuccessful transcranial MR-guided focused ultrasound (MRgFUS) ablation. The ability of alendronate treatment to modify skull bone characteristics and enhance the success rate of repeat MRgFUS procedures was assessed. Methods: Five patients with initially unsuccessful MRg…

On the performance of machine-learning assisted Monte Carlo in sampling from simple statistical physics models
Luca Maria Del Bono, Federico Ricci-Tersenghi, Francesco Zamponi
https://arxiv.org/abs/2505.22598

On the performance of machine-learning assisted Monte Carlo in sampling from simple statistical physics models
Recent years have seen a rise in the application of machine learning techniques to aid the simulation of hard-to-sample systems that cannot be studied using traditional methods. Despite the introduction of many different architectures and procedures, a wide theoretical understanding is still lacking, with the risk of suboptimal implementations. As a first step to address this gap, we provide here a complete analytic study of the widely-used Sequential Tempering procedure applied to a shallow MA…

Locally Differentially Private Two-Sample Testing
Alexander Kent, Thomas B. Berrett, Yi Yu
https://arxiv.org/abs/2505.24811 https://a…

Locally Differentially Private Two-Sample Testing
We consider the problem of two-sample testing under a local differential privacy constraint where a permutation procedure is used to calibrate the tests. We develop testing procedures which are optimal up to logarithmic factors, for general discrete distributions and continuous distributions subject to a smoothness constraint. Both non-interactive and interactive tests are considered, and we show allowing interactivity results in an improvement in the minimax separation rates. Our results show …

HumanRAM: Feed-forward Human Reconstruction and Animation Model using Transformers
Zhiyuan Yu, Zhe Li, Hujun Bao, Can Yang, Xiaowei Zhou
https://arxiv.org/abs/2506.03118

HumanRAM: Feed-forward Human Reconstruction and Animation Model using Transformers
3D human reconstruction and animation are long-standing topics in computer graphics and vision. However, existing methods typically rely on sophisticated dense-view capture and/or time-consuming per-subject optimization procedures. To address these limitations, we propose HumanRAM, a novel feed-forward approach for generalizable human reconstruction and animation from monocular or sparse human images. Our approach integrates human reconstruction and animation into a unified framework by introdu…

This https://arxiv.org/abs/2302.00469 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

Regression Adjustment, Cross-Fitting, and Randomized Experiments with Many Controls
This paper studies estimation and inference for average treatment effects in randomized experiments with many covariates, under a design-based framework with a deterministic number of treated units. We show that a simple yet powerful cross-fitted regression adjustment achieves bias-correction and leads to sharper asymptotic properties than existing alternatives. Specifically, we derive higher-order stochastic expansions, analyze associated inference procedures, and propose a modified HC3 varian…