Bayesian Flow Networks for Offline Trajectory Planning

arXiv:2608.25163 · cs.LG, cs.AI · Submitted 2026-08-25 · Read on arXiv

cs.LG, cs.AI

Submitted: 2026-08-25

Updated: 2026-08-25

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 22× in this paper · explained in 8 episodes
• Diffusion Models — 18× in this paper · explained in 6 episodes
• Reinforcement Learning — 16× in this paper · explained in 4 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Generative Model — 6× in this paper · explained in 2 episodes
• Generative Modeling — 4× in this paper · explained in 3 episodes
• Loss Function — 4× in this paper · explained in 2 episodes
• Reinforcement Learning (RL) — 4× in this paper · explained in 25 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Adam — 3× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• In International Conference on Machine Learning — 2× in this paper
• U-net architecture — 2× in this paper · explained in 3 episodes
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Diffusion Process — 1× in this paper · explained in 2 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Markov Decision Process (MDP) — 1× in this paper · explained in 11 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Structured Denoising Diffusion Models in Discrete State-Spaces
• D4RL: Datasets for Deep Data-Driven Reinforcement Learning
• Bayesian Flow Networks
• Adam: A Method for Stochastic Optimization
• Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
• Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution

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