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arXiv:2602.15030v1 Announce Type: new Abstract: We introduce the Sphere Encoder, an efficient generative framework capable of producing images in a single forward pass and competing...
arXiv:2602.15031v1 Announce Type: new Abstract: High-fidelity generative video editing has seen significant quality improvements by leveraging pre-trained video foundation models. However, their computational cost is...
arXiv:2504.18880v3 Announce Type: cross Abstract: Accurately identifying the synthesis conditions of metal-organic frameworks (MOFs) is essential for guiding experimental design, yet remains challenging because relevant...
arXiv:2602.12666v1 Announce Type: cross Abstract: Using clean numerical simulation (CNS) which can give very accurate spatiotemporal trajectory of Navier-Stokes turbulence in a finite but long...
arXiv:2602.13249v1 Announce Type: cross Abstract: Foundation models in molecular learning have advanced along two parallel tracks: protein models, which typically utilize evolutionary information to learn...
arXiv:2602.13265v1 Announce Type: cross Abstract: With the development of sixth-generation (6G) wireless communication networks, the security challenges are becoming increasingly prominent, especially for mobile users...
arXiv:2602.13270v1 Announce Type: cross Abstract: Pneumonia is a serious global health problem, contributing to high morbidity and mortality, especially in areas with limited diagnostic tools...
arXiv:2602.13276v1 Announce Type: cross Abstract: Inspired by recently developed Fokker--Planck models for Bose--Einstein statistics, we study a consensus formation model with condensation effects driven by...
arXiv:2602.13308v1 Announce Type: cross Abstract: Medical image analysis requires substantial labeled data for model training, yet expert annotation is expensive and time-consuming. Active learning (AL)...
arXiv:2602.13325v1 Announce Type: cross Abstract: Graph neural networks trained to predict observable dynamics can be used to decompose the temporal activity of complex heterogeneous systems...
arXiv:2602.13346v1 Announce Type: cross Abstract: Single-cell RNA-seq (scRNA-seq) enables atlas-scale profiling of complex tissues, revealing rare lineages and transient states. Yet, assigning biologically valid cell...
arXiv:2602.13362v1 Announce Type: cross Abstract: A key challenge in probabilistic regression is ensuring that predictive distributions accurately reflect true empirical uncertainty. Minimizing overall prediction error...
arXiv:2602.13410v1 Announce Type: cross Abstract: Landauer's principle bounds the heat generated by logical operations, but in practice the thermodynamic cost of computation is dominated by...
arXiv:2602.13414v1 Announce Type: cross Abstract: Implicit neural representations (INRs) have emerged as powerful tools for encoding signals, yet dominant MLP-based designs often suffer from slow...
arXiv:2602.13419v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown remarkable potential in scientific domains like retrosynthesis; yet, they often lack the fine-grained control...
arXiv:2602.13421v1 Announce Type: cross Abstract: Computation in biological systems is fundamentally energy-constrained, yet standard theories of computation treat energy as freely available. Here, we argue...
arXiv:2602.13472v1 Announce Type: cross Abstract: The Discrete Fourier Transform (DFT) is central to the analysis of uniformly sampled signals, yet many practical applications involve non-uniform...
arXiv:2602.13494v1 Announce Type: cross Abstract: Integer Linear Programs (ILPs) are a flexible and ubiquitous model for discrete optimization problems. Solving ILPs is \textsf{NP-Hard} yet of...
arXiv:2602.13499v1 Announce Type: cross Abstract: Collective decision-making can be viewed as the problem of aggregating multiple noisy information channels about an unknown state of the...
arXiv:2602.13510v1 Announce Type: cross Abstract: We are concerned with optimization in a broad sense through the lens of solving variational inequalities (VIs) -- a class...
arXiv:2602.13513v1 Announce Type: cross Abstract: In this work, we investigate the use of data-driven equation discovery for dynamical systems to model and forecast continuous-time dynamics...
arXiv:2602.13522v1 Announce Type: cross Abstract: While Mamba models offer efficient sequence modeling, vanilla versions struggle with temporal correlations and boundary details in Arctic sea ice...
arXiv:2602.13565v1 Announce Type: cross Abstract: Stochastic differential equations (SDEs) offer powerful and accessible mathematical models for capturing both deterministic and probabilistic aspects of dynamic behavior...
arXiv:2602.13615v1 Announce Type: cross Abstract: This paper provides two results that are useful in the study of the existence and the stability properties of a...