Category
arXiv:2602.16181v1 Announce Type: new Abstract: Energy theft poses a significant threat to the stability and efficiency of smart grids, leading to substantial economic losses and …
arXiv:2602.16188v1 Announce Type: new Abstract: LLM-for-time series (TS) methods typically treat time shallowly, injecting positional or prompt-based cues once at the input of a largely …
arXiv:2602.16193v1 Announce Type: new Abstract: Several complex physical systems are governed by multi-scale partial differential equations (PDEs) that exhibit both smooth low-frequency components and localized …
arXiv:2602.16196v1 Announce Type: new Abstract: Coordinating large populations of interacting agents is a central challenge in multi-agent reinforcement learning (MARL), where the size of the …
arXiv:2602.16197v1 Announce Type: new Abstract: Multimodal systems are vulnerable to partial or complete loss of input channels at deployment, which undermines reliability in real-world settings. …
arXiv:2602.16198v1 Announce Type: new Abstract: Adaptation methods have been a workhorse for unlocking the transformative power of pre-trained diffusion models in diverse applications. Existing approaches …
arXiv:2602.16204v1 Announce Type: new Abstract: Neurochaos Learning (NL) has shown promise in recent times over traditional deep learning due to its two key features: ability …
arXiv:2602.16209v1 Announce Type: new Abstract: Neural operators offer an effective framework for learning solutions of partial differential equations for many physical systems in a resolution-invariant …
arXiv:2602.16213v1 Announce Type: new Abstract: This paper introduces a novel approach to sea ice modeling using Graph Neural Networks (GNNs), utilizing the natural graph structure …
arXiv:2602.16216v1 Announce Type: new Abstract: Deep learning has improved automated electrocardiogram (ECG) classification, but limited insight into prediction reliability hinders its use in safety-critical settings. …
arXiv:2602.16217v1 Announce Type: new Abstract: Surface extraction from implicit neural representations modelling a single class surface is a well-known task. However, there exist no surface …
arXiv:2602.16218v1 Announce Type: new Abstract: Bayesian quadrature is a probabilistic, model-based approach to numerical integration, the estimation of intractable integrals, or expectations. Although Bayesian quadrature …
