#Scientific Computing

Articles (16)

• 🇺🇸 Sparse-Aware Neural Networks for Nonlinear Functionals: Mitigating the Exponential Dependence on Dimension — 09/04/2026 [USA]

  arXiv:2604.06774v1 Announce Type: cross Abstract: Deep neural networks have emerged as powerful tools for learning operators defined over infinite-dimensional function spaces. However, existing theor...

  Related: #Machine Learning Theory, #Algorithmic Efficiency
• 🇺🇸 Ontology-based knowledge graph infrastructure for interoperable atomistic simulation data — 09/04/2026 [USA]

  arXiv:2604.06230v1 Announce Type: cross Abstract: The reuse of atomistic simulation data is often limited by heterogeneous formats, incomplete metadata, and a lack of standardized representations of ...

  Related: #Data Interoperability, #Materials Science
• 🇺🇸 Learning the Stellar Structure Equations via Self-supervised Physics-Informed Neural Networks — 09/04/2026 [USA]

  arXiv:2604.06255v1 Announce Type: cross Abstract: Stellar astrophysics relies critically on accurate descriptions of the physical conditions inside stars. Traditional solvers such as \texttt{MESA} (M...

  Related: #Artificial Intelligence, #Computational Astrophysics
• 🇺🇸 Plasma GraphRAG: Physics-Grounded Parameter Selection for Gyrokinetic Simulations — 09/04/2026 [USA]

  arXiv:2604.06279v1 Announce Type: cross Abstract: Accurate parameter selection is fundamental to gyrokinetic plasma simulations, yet current practices rely heavily on manual literature reviews, leadi...

  Related: #Artificial Intelligence, #Plasma Physics
• 🇺🇸 Gradient-Informed Temporal Sampling Improves Rollout Accuracy in PDE Surrogate Training — 20/03/2026 [USA]

  arXiv:2603.18237v1 Announce Type: cross Abstract: Researchers train neural simulators on uniformly sampled numerical simulation data. But under the same budget, does systematically sampled data provi...

  Related: #Machine Learning
• 🇺🇸 scicode-lint: Detecting Methodology Bugs in Scientific Python Code with LLM-Generated Patterns — 19/03/2026 [USA]

  arXiv:2603.17893v1 Announce Type: cross Abstract: Methodology bugs in scientific Python code produce plausible but incorrect results that traditional linters and static analysis tools cannot detect. ...

  Related: #Code Quality
• 🇺🇸 An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc — 18/03/2026 [USA]

  arXiv:2603.15976v1 Announce Type: new Abstract: While large language models have significantly accelerated scientific code generation, comprehensively evaluating the generated code remains a major ch...

  Related: #AI Evaluation
• 🇺🇸 OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning — 18/03/2026 [USA]

  arXiv:2603.15797v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated exceptional logical reasoning capabilities but frequently struggle with the continuous spatiotemporal ...

  Related: #AI Research
• 🇺🇸 Intrinsic Numerical Robustness and Fault Tolerance in a Neuromorphic Algorithm for Scientific Computing — 12/03/2026 [USA]

  arXiv:2603.10246v1 Announce Type: cross Abstract: The potential for neuromorphic computing to provide intrinsic fault tolerance has long been speculated, but the brain's robustness in neuromorphic ap...

  Related: #Neuromorphic Computing
• 🇺🇸 Diversity-Aware Adaptive Collocation for Physics-Informed Neural Networks via Sparse QUBO Optimization and Hybrid Coresets — 10/03/2026 [USA]

  arXiv:2603.06761v1 Announce Type: cross Abstract: Physics-Informed Neural Networks (PINNs) enforce governing equations by penalizing PDE residuals at interior collocation points, but standard colloca...

  Related: #Machine Learning
• 🇺🇸 JAWS: Enhancing Long-term Rollout of Neural Operators via Spatially-Adaptive Jacobian Regularization — 09/03/2026 [USA]

  arXiv:2603.05538v1 Announce Type: cross Abstract: Data-driven surrogate models improve the efficiency of simulating continuous dynamical systems, yet their autoregressive rollouts are often limited b...

  Related: #Machine Learning
• 🇺🇸 MOOSEnger -- a Domain-Specific AI Agent for the MOOSE Ecosystem — 06/03/2026 [USA]

  arXiv:2603.04756v1 Announce Type: new Abstract: MOOSEnger is a tool-enabled AI agent tailored to the Multiphysics Object-Oriented Simulation Environment (MOOSE). MOOSE cases are specified in HIT ".i"...

  Related: #AI Agents
• 🇺🇸 CryoNet.Refine: A One-step Diffusion Model for Rapid Refinement of Structural Models with Cryo-EM Density Map Restraints — 27/02/2026 [USA]

  arXiv:2602.22263v1 Announce Type: cross Abstract: High-resolution structure determination by cryo-electron microscopy (cryo-EM) requires the accurate fitting of an atomic model into an experimental d...

  Related: #Artificial Intelligence, #Structural Biology
• 🇺🇸 Grounding LLMs in Scientific Discovery via Embodied Actions — 25/02/2026 [USA]

  arXiv:2602.20639v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown significant potential in scientific discovery but struggle to bridge the gap between theoretical reasoning and ...

  Related: #Artificial Intelligence, #Machine Learning
• 🇺🇸 PuYun-LDM: A Latent Diffusion Model for High-Resolution Ensemble Weather Forecasts — 16/02/2026 [USA]

  arXiv:2602.11807v2 Announce Type: replace Abstract: Latent diffusion models (LDMs) suffer from limited diffusability in high-resolution (<=0.25{\deg}) ensemble weather forecasting, where diffusabilit...

  Related: #Artificial Intelligence in Meteorology, #Weather Forecasting Technology
• 🇺🇸 Prior-Guided Symbolic Regression: Towards Scientific Consistency in Equation Discovery — 16/02/2026 [USA]

  arXiv:2602.13021v1 Announce Type: cross Abstract: Symbolic Regression (SR) aims to discover interpretable equations from observational data, with the potential to reveal underlying principles behind ...

  Related: #Machine Learning, #Mathematical Modeling