4 citations · 12 across the 11 of their papers we have counts for
3 papers · 1 filter
Scaling Online Optimal Transport Minibatches for Flow Matching
Peter Chen, Sergey Levine
A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, this stability depends critically on how source samples are paire…
Offline Materials Optimization with CliqueFlowmer
Jakub Grudzien Kuba, Benjamin Kurt Miller, Sergey Levine +1
Recent advances in deep learning inspired neural network-based approaches to computational materials discovery (CMD). A plethora of problems in this field involve finding materials…
Bridging the Simulation-to-Experiment Gap with Generative Models using Adversarial Distribution Alignment
Kai Nelson, Tobias Kreiman, Sergey Levine +1
A fundamental challenge in science and engineering is the simulation-to-experiment gap. While we often possess prior knowledge of physical laws, these physical laws can be too diff…