Video Lectures: Physics Informed ML for Modeling, Planning, and Control
caglar_ee · x · 2026-07-22
This post shares a series of video lectures on Physics Informed Machine Learning. The course focuses on applying this technology to the modeling, planning, control, and estimation of physical systems, presented by Mattia Piccinini and Gastone Pietro Rosati Papini.
Related event: Video Course Covers Physics-Informed ML for Modeling and Control(2 posts)→
More from Research
- BrowseComp-Plus benchmarks deep-research agents and highlights 9-turn production systems — IgorCarron · 2026-07-22
- Psychology Today spotlights a paper arguing LLMs do not think like humans — ValerioCapraro · 2026-07-22
- Area Chair Reports: Reviewer Accountability Working, Emergency Recruits at Record Low — GuestCheap9405 · 2026-07-22
- Recursive self-improvement in AI shifts from bounded refinement to autonomous research loops — theomitsa · 2026-07-22
- A reposted AGI architecture blueprint points to system design for future general intelligence — theomitsa · 2026-07-22
- ASR paper boosts German disfluency F1 from 10% to 79% with verbatim control — nyralabs · 2026-07-22