AINewsnow

Feature tracking in physics-informed neural networks via joint optimization of nonlinear deformation manifolds: application to shocks

arXiv:2610.02230v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) often converge to inaccurate solutions for conservation laws with shocks, because uniformly distributed collocation points undersample localized features and let the residual be dominated by regions that are…

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-10-05 04:00 · arXiv stat.ML
    Feature tracking in physics-informed neural networks via joint optimization of nonlinear deformation manifolds: application to shocks

More stories

  1. NVIDIA DGX Spark 64GB Gives Developers More Ways to Build and Scale Local AI — NVIDIA Blog
  2. Trump’s big AI move: ‘Super Intelligence Force’ launched, Jay Clayton named AI czar — Mint AI
  3. A model guide for the GPT-6 family — OpenAI News
  4. An OpenAI safety employee has quit and is sounding the alarm — The Verge AI
  5. Introducing Oscilloscope Diffusion — r/comfyui
  6. OpenAI fires 3 AI safety researchers for allegedly sharing confidential company information — Mint AI
  7. Apple says it's tightening macOS Full Disk Access' controls due to new risks from AI agents — TechCrunch AI
  8. Strata is seriously impressive, running Qwen 3.8 Flash Next on hermes at 512k context. — r/LocalLLM

Get the daily brief of stories like this at 6:30 every morning →