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arXiv:2603.03610v1 Announce Type: new Abstract: Understanding how systems built out of modular components can be jointly optimized is an important problem in biology, engineering, and …
arXiv:2603.03612v1 Announce Type: new Abstract: The community is increasingly exploring linear RNNs (LRNNs) as language models, motivated by their expressive power and parallelizability. While prior …
arXiv:2603.03621v1 Announce Type: new Abstract: We develop a rigorous framework for extending neural operators to handle out-of-distribution input functions. We leverage kernel approximation techniques and …
arXiv:2603.03650v1 Announce Type: new Abstract: Physical dynamical systems can be viewed as natural information processors: their systems preserve, transform, and disperse input information. This perspective …
arXiv:2603.03651v1 Announce Type: new Abstract: Freezing of Gait (FOG) is a debilitating motor symptom commonly experienced by individuals with Parkinson's Disease (PD) which often leads …
arXiv:2603.03662v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as a powerful framework for processing graph-structured data. However, conventional GNNs and their variants …
arXiv:2603.03672v1 Announce Type: new Abstract: The Shapley value provides a principled foundation for data valuation, but exact computation is #P-hard due to the exponential coalition …
arXiv:2603.03673v1 Announce Type: new Abstract: Stein's identity is a fundamental tool in machine learning with applications in generative models, stochastic optimization, and other problems involving …
arXiv:2603.03725v1 Announce Type: new Abstract: The volume of freely scraped data on the Internet has driven the tremendous success of deep learning. Along with this …
arXiv:2603.03748v1 Announce Type: new Abstract: High-stakes synthetic data generation faces a fundamental Quadrilemma: achieving Fidelity to the original distribution, Control over complex logical constraints, Reliability …
arXiv:2603.03756v1 Announce Type: new Abstract: While large language models (LLMs) show promise in scientific discovery, existing research focuses on inference or feedback-driven training, leaving the …
arXiv:2603.03760v1 Announce Type: new Abstract: Time Series forecasting (TSF) in the modern era faces significant computational and storage cost challenges due to the massive scale …