2 papers
cs.LG2025
Maximizing Efficiency of Dataset Compression for Machine Learning Potentials With Information Theory
Benjamin Yu, Vincenzo Lordi, Daniel Schwalbe-Koda
Machine learning interatomic potentials (MLIPs) balance high accuracy and lower costs compared to density functional theory calculations, but their performance often depends on the…
cs.CV2025
Smart-GRPO: Smartly Sampling Noise for Efficient RL of Flow-Matching Models
Benjamin Yu, Jackie Liu, Justin Cui
Recent advancements in flow-matching have enabled high-quality text-to-image generation. However, the deterministic nature of flow-matching models makes them poorly suited for rein…