AINewsnow

New method adds physical closure to data-driven equation discovery

This story is from 2026-11-06. It is preserved in the archive; the latest stories are on the live feed.

A paper on arXiv proposes literature-informed dimensionless learning to make data-discovered equations physically consistent across operating conditions, addressing unresolved coefficient dependence.

Read the full story at arXiv stat.ML ↗

Timeline · 1 report

  1. 2026-11-06 05:00 · arXiv stat.ML
    Discovering like a scientist: Literature-informed dimensionless learning for physical closure of data-driven equations

More stories

  1. OpenAI to keep expanding AI data centers despite election results favoring restrictions — DigiTimes Asia
  2. Claude Code adoption spreads from finance tools to restaurants and smart homes — DEV Community — AI
  3. US AI Safety Center Staff Now Report to White House, Raising Independence Concerns — AP News
  4. Hydra-PSIE expands 'Coeziune OM–IA' DOI registry to 38 published works — DEV Community — AI
  5. SemiAnalysis details rapid buildout of AI data center region in Inner Mongolia — Techmeme
  6. AI Coding Agents Shift From Prompt Files to Deterministic Scripts and Sandboxed Execution — DEV Community — AI
  7. Tencent AI chief warns AI will soon master biology, raising safety risks — SCMP China Tech
  8. Dev News Digest: OpenSSH advisory, Claude Code email leak, GitHub Actions lockfiles GA — DEV Community — AI

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