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arXiv:2603.04606v1 Announce Type: new Abstract: PDE foundation models are typically pretrained on large, diverse corpora of PDE datasets and can be adapted to new settings …
arXiv:2603.04625v1 Announce Type: new Abstract: This work establishes a rigorous variational and gradient-based equivalence between the classical K-Means algorithm and differentiable Radial Basis Function (RBF) …
arXiv:2603.04648v1 Announce Type: new Abstract: Real-world reinforcement learning systems must operate under distributional drift in their observation streams, yet most policy architectures implicitly assume fully …
arXiv:2603.04663v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) architectures fail in high-stakes financial domains due to two fundamental limitations: the inherent arithmetic incompetence of …
arXiv:2603.04683v1 Announce Type: new Abstract: Accurate estimation of forest biomass is crucial for monitoring carbon sequestration and informing climate change mitigation strategies. Existing methods often …
arXiv:2603.04692v1 Announce Type: new Abstract: Predictive modeling in engineering applications has long been dominated by bespoke models and small, siloed tabular datasets, limiting the applicability …
arXiv:2603.04703v1 Announce Type: new Abstract: We study matrix completion via deep matrix factorization (a.k.a. deep linear neural networks) as a simplified testbed to examine how …
arXiv:2603.04715v1 Announce Type: new Abstract: "Dreaming" enables agents to learn from imagined experiences, enabling more robust and sample-efficient learning of world models. In this work, …
arXiv:2603.04730v1 Announce Type: new Abstract: Many modern biological assays, including RNA sequencing, yield integer-valued counts that reflect the number of molecules detected. These measurements are …
arXiv:2603.04731v1 Announce Type: new Abstract: Unlearnable Examples (UEs) serve as a data protection strategy that generates imperceptible perturbations to mislead models into learning spurious correlations …
arXiv:2603.04736v1 Announce Type: new Abstract: Learning a transport model that maps a source distribution to a target distribution is a canonical problem in machine learning, …
arXiv:2603.04755v1 Announce Type: new Abstract: Obstructive sleep apnea (OSA) is a sleep disorder that affects nearly one billion people globally and significantly elevates cardiovascular risk. …