Tootfinder

I’ve long thought that top govt folks (the elected ones) should have the same healthcare/pension as the poorest citizen.
And take transit to work. https://mastodon.social/@VeroniqueB99/114797404531262958

Vee (@VeroniqueB99@mastodon.social)
Attached: 1 image Let them eat cake.

This https://arxiv.org/abs/2502.00722 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDC_…

Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
Recent advancements in Large Language Models (LLMs) have led to increasingly diverse requests, accompanied with varying resource (compute and memory) demands to serve them. However, this in turn degrades the cost-efficiency of LLM serving as common practices primarily rely on homogeneous GPU resources. In response to this problem, this work conducts a thorough study about serving LLMs over heterogeneous GPU resources on cloud platforms. The rationale is that different GPU types exhibit distinct…

Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
Yiheng Lin, Christopher Yeh, Zaiwei Chen, Adam Wierman
https://arxiv.org/abs/2506.04497

Maximizing the Value of Predictions in Control: Accuracy Is Not Enough
We study the value of stochastic predictions in online optimal control with random disturbances. Prior work provides performance guarantees based on prediction error but ignores the stochastic dependence between predictions and disturbances. We introduce a general framework modeling their joint distribution and define "prediction power" as the control cost improvement from the optimal use of predictions compared to ignoring the predictions. In the time-varying Linear Quadratic Regulator (LQR) s…

Upper bound of transient growth in accelerating and decelerating wall-driven flows using the Lyapunov method
Zhengyang Wei, Weichen Zhao, Chang Liu
https://arxiv.org/abs/2508.01410

Upper bound of transient growth in accelerating and decelerating wall-driven flows using the Lyapunov method
This work analyzes accelerating and decelerating wall-driven flows by quantifying the upper bound of transient energy growth using a Lyapunov-type approach. By formulating the linearized Navier-Stokes equations as a linear time-varying system and constructing a time-dependent Lyapunov function, we obtain a rigorous upper bound on transient energy growth by solving linear matrix inequalities (LMI). The LMI approach can obtain the upper bound of transient energy growth that closely matches transi…

Tensor-based multivariate function approximation: methods benchmarking and comparison
Athanasios C. Antoulas, Ion Victor Gosea, Charles Poussot-Vassal, Pierre Vuillemin
https://arxiv.org/abs/2506.04791

Tensor-based multivariate function approximation: methods benchmarking and comparison
In this note, we evaluate the performances, the features and the user-experience of some methods (and their implementations) designed for tensor- (or data-) based multivariate function construction and approximation. To this aim, a collection of multivariate functions extracted from contributive works coming from different communities, is suggested. First, these functions with varying complexity (e.g. number and degree of the variables) and nature (e.g. rational, irrational, differentiable or n…

Uncertainty Estimation for Novel Views in Gaussian Splatting from Primitive-Based Representations of Error and Visibility
Thomas Gottwald, Edgar Heinert, Matthias Rottmann
https://arxiv.org/abs/2508.02443

Uncertainty Estimation for Novel Views in Gaussian Splatting from Primitive-Based Representations of Error and Visibility
In this work, we present a novel method for uncertainty estimation (UE) in Gaussian Splatting. UE is crucial for using Gaussian Splatting in critical applications such as robotics and medicine. Previous methods typically estimate the variance of Gaussian primitives and use the rendering process to obtain pixel-wise uncertainties. Our method establishes primitive representations of error and visibility of trainings views, which carries meaningful uncertainty information. This representation is o…

Can Large Pretrained Depth Estimation Models Help With Image Dehazing?
Hongfei Zhang, Kun Zhou, Ruizheng Wu, Jiangbo Lu
https://arxiv.org/abs/2508.00698 https://

Can Large Pretrained Depth Estimation Models Help With Image Dehazing?
Image dehazing remains a challenging problem due to the spatially varying nature of haze in real-world scenes. While existing methods have demonstrated the promise of large-scale pretrained models for image dehazing, their architecture-specific designs hinder adaptability across diverse scenarios with different accuracy and efficiency requirements. In this work, we systematically investigate the generalization capability of pretrained depth representations-learned from millions of diverse image…

TDCOSMO 2025: Cosmological constraints from strong lensing time delays
Simon Birrer, Elizabeth J. Buckley-Geer, Michele Cappellari, Frederic Courbin, Frederic Dux, Christopher D. Fassnacht, Joshua A. Frieman, Aymeric Galan, Daniel Gilman, Xiang-Yu Huang, Shawn Knabel, Danial Langeroodi, Huan Lin, Martin Millon, Takahiro Morishita, Veronica Motta, Pritom Mozumdar, Eric Paic, Anowar J. Shajib, William Sheu, Dominique Sluse, Alessandro Sonnenfeld, Chiara Spiniello, Massimo Stiavelli, Sher…

TDCOSMO 2025: Cosmological constraints from strong lensing time delays
We present cosmological constraints from 8 strongly lensed quasars (hereafter, the TDCOSMO-2025 sample). Building on previous work, our analysis incorporated new deflector stellar velocity dispersions measured from spectra obtained with the James Webb Space Telescope (JWST), the Keck Telescopes, and the Very Large Telescope (VLT), utilizing improved methods. We used integrated JWST stellar kinematics for 5 lenses, VLT-MUSE for 2, and resolved kinematics from Keck and JWST for RX J1131-1231. We …

Reposted with alt
https://mastodon.social/@VeroniqueB99/114604050608739836

Vee (@VeroniqueB99@mastodon.social)
Attached: 1 image

Using Code Snippets to Teach Programming Languages
Joshua Akingbade, Jianhua Yang, Mir Seyedebrahimi
https://arxiv.org/abs/2506.00404 https://

Using Code Snippets to Teach Programming Languages
Coding is a fundamental skill required in the engineering discipline, and much work exists exploring better ways of teaching coding in the higher education context. In particular, Code Snippets (CSs) are approved to be an effective way of introducing programming language units to students. CSs are portions of source code of varying size and content. They can be used in a myriad of ways, one of which is to teach the code they contain as well as its function. To further explore the use of CSs, a …