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Seungyeon Choi

2 accepted papers

2026

LeakGFN: Robust Molecular Generation in Generative Flow Networks via Flow Decomposition

ICML 2026poster

Generative Flow Networks (GFlowNets) have emerged as a powerful framework for molecular generation, sampling diverse candidates proportionally to a reward function. However, the vast chemical space necessitates truncating trajectory length, forcing models to treat incomplete molecular fragments as t…

Cited by 0SourceScholar
2025

Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration

NeurIPS 2025poster

Recent advances in Structure-based Drug Design (SBDD) have leveraged generative models for 3D molecular generation, predominantly evaluating model performance by binding affinity to target proteins. However, practical drug discovery necessitates high binding affinity along with synthetic feasibility…

Cited by 0SourceScholar