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arXiv:2602.21160v1 Announce Type: cross Abstract: In safety-critical classification, the cost of failure is often asymmetric, yet Bayesian deep learning summarises epistemic uncertainty with a single...
arXiv:2204.10169v4 Announce Type: replace Abstract: This paper studies algorithms for computing a Gomory-Hu tree, which is a classical data structure that compactly stores all minimum...
arXiv:2207.10230v2 Announce Type: replace Abstract: This paper studies optimal linear power control for battery-limited energy harvesting communications. It provides a systematic analysis of linear power...
arXiv:2208.02000v3 Announce Type: replace Abstract: The Gomory-Hu tree, or a cut tree, is a classic data structure that stores minimum $s$-$t$ cuts of an undirected...
arXiv:2208.02500v2 Announce Type: replace Abstract: Programmable Logic Controllers (PLCs) drive industrial processes critical to society, for example, water treatment and distribution, electricity and fuel networks....
arXiv:2303.01633v4 Announce Type: replace Abstract: Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation (6G) networks, providing ubiquitous, continuous, and scalable...
arXiv:2309.13411v3 Announce Type: replace Abstract: This paper focuses on the fundamental challenge of partitioning input variables in attribution methods for Explainable AI, particularly in Shapley...
arXiv:2310.01254v5 Announce Type: replace Abstract: Guarded Monotone Strict NP (GMSNP) extends Monotone Monadic Strict NP (MMSNP) by guarded existentially quantified predicates of arbitrary arities. We...
arXiv:2311.16953v5 Announce Type: replace Abstract: The goal of local certification is to locally convince the vertices of a graph $G$ that $G$ satisfies a given...
arXiv:2401.07390v2 Announce Type: replace Abstract: Self-attention transformers have demonstrated accuracy for image classification with smaller data sets. However, a limitation is that tests to-date are...
arXiv:2401.07806v3 Announce Type: replace Abstract: Optimal experimental design (OED) aims to choose the observations in an experiment to be as informative as possible, according to...
arXiv:2402.02667v2 Announce Type: replace Abstract: Physics-Informed Neural Networks (PINNs) encounter accuracy limitations when solving the Allen--Cahn (AC) and Cahn--Hilliard (CH) partial differential equations (PDEs). To...
arXiv:2405.10385v3 Announce Type: replace Abstract: The SemEval 2024 BRAINTEASER task challenges language models to perform lateral thinking -- a form of creative, non-linear reasoning that...
arXiv:2406.10281v5 Announce Type: replace Abstract: Recent progress in large language models enables the creation of realistic machine-generated content. Watermarking is a promising approach to distinguish...
arXiv:2406.11935v3 Announce Type: replace Abstract: Large Language Models (LLMs) have shown remarkable capabilities in solving various programming tasks, such as code generation. However, their potential...
arXiv:2407.00575v3 Announce Type: replace Abstract: Consider a strongly monotone game where the players' utility functions include a reward function and a linear term for each...
arXiv:2407.08019v2 Announce Type: replace Abstract: With the advancements in denoising diffusion probabilistic models (DDPMs), image inpainting has significantly evolved from merely filling information based on...
arXiv:2408.07016v3 Announce Type: replace Abstract: Representation learning is an approach that allows to discover and extract the factors of variation from the data. Intuitively, a...
arXiv:2409.00618v3 Announce Type: replace Abstract: Existing 3D multi-object tracking (MOT) methods often sacrifice efficiency and generalizability for robustness, largely relying on complex association metrics derived...
arXiv:2409.14719v4 Announce Type: replace Abstract: We aim to solve the problem of generating coarse-to-fine skills learning from demonstrations (LfD). To scale precision, traditional LfD approaches...
arXiv:2411.00759v4 Announce Type: replace Abstract: Discrete flow matching, a recent framework for modeling categorical data, has shown competitive performance with autoregressive models. However, unlike continuous...
arXiv:2412.00445v2 Announce Type: replace Abstract: We consider the problem of surface segmentation, where the goal is to partition a surface represented by a triangular mesh....
arXiv:2412.06871v2 Announce Type: replace Abstract: In the context of rail transit operations, real-time passenger flow prediction is essential; however, most models primarily focus on normal...
arXiv:2412.09238v4 Announce Type: replace Abstract: Model Predictive Control (MPC) has demonstrated significant potential in improving energy efficiency in building climate control, outperforming traditional controllers commonly...