1 citations · 1 across the 6 of their papers we have counts for
3 papers · 1 filter
Learning Collective Variables from BioEmu with Time-Lagged Generation
Seonghyun Park, Kiyoung Seong, Soojung Yang +2
Molecular dynamics is crucial for understanding molecular systems but its applicability is often limited by the vast timescales of rare events like protein folding. Enhanced sampli…
Energy-based generator matching: A neural sampler for general state space
Dongyeop Woo, Minsu Kim, Minkyu Kim +2
We propose Energy-based generator matching (EGM), a modality-agnostic approach to train generative models from energy functions in the absence of data. Extending the recently propo…
On scalable and efficient training of diffusion samplers
Minkyu Kim, Kiyoung Seong, Dongyeop Woo +2
We address the challenge of training diffusion models to sample from unnormalized energy distributions in the absence of data, the so-called diffusion samplers. Although these appr…