Learning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation 事件

Learning Implicit Bias in Generative Spaces for Accelerating Protein Dynamics Emulation arXiv:2606.01833v1 Announce Type: cross Abstract: Generative emulators of protein dynamics produce plausible trajectories at a fraction of the cost of molecular dynamics, but they inherit their training distribution and tend to revisit known states rather than reach rare ones under long-horizon extrapolation. Inspired by classical enhanced sampling, we introduce an implicit, history-dependent bias in the gen