3 papers
cs.LG2025
Diffusion Self-Weighted Guidance for Offline Reinforcement Learning
Augusto Tagle, Javier Ruiz-del-Solar, Felipe Tobar
Offline reinforcement learning (RL) recovers the optimal policy given historical observations of an agent. In practice, is modeled as a weighted version of the agent's be…
cs.CV2025
Towards SFW sampling for diffusion models via external conditioning
Camilo Carvajal Reyes, JoaquÃn Fontbona, Felipe Tobar
Score-based generative models (SBM), also known as diffusion models, are the de facto state of the art for image synthesis. Despite their unparalleled performance, SBMs have recent…
stat.ML2024
Avoiding mode collapse in diffusion models fine-tuned with reinforcement learning
Roberto Barceló, Cristóbal Alcázar, Felipe Tobar
Fine-tuning foundation models via reinforcement learning (RL) has proven promising for aligning to downstream objectives. In the case of diffusion models (DMs), though RL training…