publications

(*) denotes equal contribution, (‡) denotes equal advising.

2026

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    Stochastic Optimal Control for Continuous-Time fMRI Representation Learning
    Joonhyeong Park*, Byoungwoo Park*, Chang-Bae Bang, Jungwon Choi, Hyungjin Chung, Byung-Hoon Kim‡, and Juho Lee‡
    International Conference on Learning Representations (ICLR), 2026
    PDF
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    Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces
    Byoungwoo Park, Juho Lee, and Guan-Horng Liu
    International Conference on Machine Learning (ICML), 2026
    NeurIPS 2025 Workshop on Frontiers in Probabilistic Inference
    PDF

2025

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    Improving Constrained Language Generation via Self-Distilled Twisted Sequential Monte Carlo
    Sooyeon Kim, Giung Nam, Byoungwoo Park, and Juho Lee
    NeurIPS 2025 Workshop on Frontiers in Probabilistic Inference
    PDF
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    Multi-Marginal Schrödinger Bridge Matching
    Byoungwoo Park, and Juho Lee
    Preprint
    PDF Code
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    Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
    Byoungwoo Park, Hyungi Lee, and Juho Lee
    International Conference on Learning Representations (ICLR), 2025
    Oral Presentation at ICLR 2025 [Top 1.8%]
    NeurIPS 2024 Workshop on Bayesian Decision-making and Uncertainty
    PDF Code

2024

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    Stochastic Optimal Control for Diffusion Bridges in Function Spaces
    Byoungwoo Park, Jungwon Choi, Sungbin Lim‡, and Juho Lee‡
    Advances in Neural Information Processing Systems (NeurIPS), 2024
    PDF Code

2023

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    Nerual Stochastic Differential Games for Time-Series Analysis
    Sungwoo Park*, Byoungwoo Park*, Moontae Lee, and Changhee Lee
    International Conference on Machine Learning (ICML), 2023
    PDF Code Page