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Hyeonah Kim

Postdoctorate - Université de Montréal
Co-supervisor
Research Topics
AI for Science
Combinatorial Optimization
Deep Learning
GFlowNets

Publications

Synthesizable Molecular Generation via Soft-constrained GFlowNets with Rich Chemical Priors
D. Biton
Louis Vaillancourt
Yves V. Brun
Improved Off-policy Reinforcement Learning in Biological Sequence Design
Designing biological sequences with desired properties is challenging due to vast search spaces and limited evaluation budgets. Although rei… (see more)nforcement learning methods use proxy models for rapid reward evaluation, insufficient training data can cause proxy misspecification on out-of-distribution inputs. To address this, we propose a novel off-policy search,
Ant Colony Sampling with GFlowNets for Combinatorial Optimization
We present the Generative Flow Ant Colony Sampler (GFACS), a novel meta-heuristic method that hierarchically combines amortized inference an… (see more)d parallel stochastic search. Our method first leverages Generative Flow Networks (GFlowNets) to amortize a \emph{multi-modal} prior distribution over combinatorial solution space that encompasses both high-reward and diversified solutions. This prior is iteratively updated via parallel stochastic search in the spirit of Ant Colony Optimization (ACO), leading to the posterior distribution that generates near-optimal solutions. Extensive experiments across seven combinatorial optimization problems demonstrate GFACS's promising performances.