From: NeurIPS.cc/2022/Workshop/Offline_RL/Paper47/Reviewer_5FPE
title: Review
review: The paper studies the problem of learning dynamics models for control. The proposed approach models the dynamics as an ODE, where the dynamics change is the combination of (1) a physical prior using domain knowledge and (2) a learned residual. The full model is then trained end to end with a differentiable ODE solver.

The method performs better than the fully learned model and just the physics based prior on Mujoco tasks. Overall this seems like a nice way of combining prior knowledge and learning for model-based RL.
rating: 7: Good paper, accept
confidence: 3: The reviewer is fairly confident that the evaluation is correct