Portrait of Minkyu Kim

Minkyu Kim

Independent visiting researcher - KAIST
Research Topics
AI for Science
Crystals
Generative Models
Molecular Modeling
Probabilistic Models

Publications

Energy-based generator matching: A neural sampler for general state space
Dongyeop Woo
Kiyoung Seong
Sungsoo Ahn
We propose Energy-based generator matching (EGM), a modality-agnostic approach to train generative models from energy functions in the absen… (see more)ce of data. Extending the recently proposed generator matching, EGM enables training of arbitrary continuous-time Markov processes, e.g., diffusion, flow, and jump, and can generate data from continuous, discrete, and a mixture of two modalities. To this end, we propose estimating the generator matching loss using self-normalized importance sampling with an additional bootstrapping trick to reduce variance in the importance weight. We validate EGM on both discrete and multimodal tasks up to 100 and 20 dimensions, respectively.