4 papers · 1 filter
Diffusion Fine-Tuning via Reparameterized Policy Gradient of the Soft Q-Function
Hyeongyu Kang, Jaewoo Lee, Woocheol Shin +2
Diffusion models excel at generating high-likelihood samples but often require alignment with downstream objectives. Existing fine-tuning methods for diffusion models significantly…
Diffusion Alignment as Variational Expectation-Maximization
Jaewoo Lee, Minsu Kim, Sanghyeok Choi +7
Diffusion alignment aims to optimize diffusion models for the downstream objective. While existing methods based on reinforcement learning or direct backpropagation achieve conside…
Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization
Kiyoung Om, Kyuil Sim, Taeyoung Yun +2
Optimizing high-dimensional black-box functions under black-box constraints is a pervasive task in a wide range of scientific and engineering problems. These problems are typically…
Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization
Taeyoung Yun, Kiyoung Om, Jaewoo Lee +2
Optimizing high-dimensional and complex black-box functions is crucial in numerous scientific applications. While Bayesian optimization (BO) is a powerful method for sample-efficie…