Ever get tired of tiny timesteps bottlenecking your MD simulations?
We show how to train a model for large-timestep Hamiltonian dynamics directly on standard MLFF datasets. ๐ก๐ผ ๐ฟ๐ฒ๐ณ๐ฒ๐ฟ๐ฒ๐ป๐ฐ๐ฒ ๐๐ฟ๐ฎ๐ท๐ฒ๐ฐ๐๐ผ๐ฟ๐ถ๐ฒ๐, ๐ป๐ผ ๐๐ป๐ฟ๐ผ๐น๐น๐ถ๐ป๐ด, ๐ป๐ผ ๐๐ฒ๐ฎ๐ฐ๐ต๐ฒ๐ฟ needed!๐งต๐
Heading to @NeurIPSConf in SD!
๐ Weโll be presenting our latest work, DiTMC - a modular architecture for molecular conformer generation.
๐๏ธ Excited to meet new and old friends! If you want to grab a coffee and chat about generative models & AI4Science, feel free to reach out.
๐ย This is a joint work with the amazing @FrankThorben, @RipkenWinfried, Klaus-Robert Mรผller, Oliver T. Unke and Stefan Chmiela. Thank you so much for this fantastic collaboration!