PrT-Flow: Probability-Tractable Flow Matching for Reinforcement Learning
PrT-Flow (Probability-Tractable Flow Matching), which computes probability density while retaining multimodal, multi-step action generation, and demonstrates that invertible networks with tractable probability densities can learn effective robot policies and support SAC-style actor-critic training.