FP-IRL: Fokker-Planck Inverse Reinforcement Learning -- A Physics-Constrained Approach to Markov Decision Processes
"物理约束" 相关文章
Machine learning for atomic-scale simulations: balancing speed and physical laws
Quantifying constraint hierarchies in Bayesian PINNs via per-constraint Hessian decomposition
PIRF: Physics-Informed Reward Fine-Tuning for Diffusion Models
High-Resolution Global Land Surface Temperature Retrieval via a Coupled Mechanism-Machine Learning Framework
Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems
RACER: Rational Artificial Intelligence Car-following-model Enhanced by Reality
