SOTAVerified

Physics-informed machine learning

Machine learning used to represent physics-based and/or engineering models

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–60 of 192 papers

TitleStatusHype
Update hydrological states or meteorological forcings? Comparing data assimilation methods for differentiable hydrologic models—0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
Generalizable and Fast Surrogates: Model Predictive Control of Articulated Soft Robots using Physics-Informed Neural Networks—0
Understanding Generalization in Physics Informed Models through Affine Variety Dimensions—0
PDE-DKL: PDE-constrained deep kernel learning in high dimensionalityCode0
Empirical modeling and hybrid machine learning framework for nucleate pool boiling on microchannel structured surfaces—0
Physics-Informed Machine Learning for Efficient Reconfigurable Intelligent Surface Design—0
Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights—0
KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics—0
Towards Physically Interpretable World Models: Meaningful Weakly Supervised Representations for Visual Trajectory Prediction—0
Show:102550
← PrevPage 6 of 20Next →

No leaderboard results yet.