1 citations · 1 across the 8 of their papers we have counts for
10 papers
Proper Scoring Rule-based Diffusion for Probabilistic Weather Forecasting
Joonhyeong Park, Giung Nam, Hyungi Lee +3
Recent probabilistic weather forecasters train stochastic predictors with the continuous ranked probability score (CRPS) to generate each ensemble member in a single forward pass.…
LongTake: Learning to Sustain Dynamics in Long-Horizon Video Generation
Byoungwoo Park, Jaemoo Choi, Juho Lee +1
World models, game simulators, and long-take video creation require coherent scene evolution and sustained dynamics over extended durations. Autoregressive (AR) video diffusion pro…
Function-Space Diffusion for Motion Planning
Zinuo Chang, Yipu Chen, Byoungwoo Park +2
Diffusion-based motion planners have demonstrated strong performance in generating diverse and high-quality robot trajectories in cluttered environments with multiple feasible solu…
Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning
Byoungwoo Park, Utkarsh A. Mishra, Jaemoo Choi +2
Diffusion models provide strong priors for generating structured data, but many tasks require outputs beyond the scale on which these models are typically trained. Compositional ge…
Functional Adjoint Sampler: Scalable Sampling on Infinite Dimensional Spaces
Byoungwoo Park, Juho Lee, Guan-Horng Liu
Learning-based methods for sampling from the Gibbs distribution in finite-dimensional spaces have progressed quickly, yet theory and algorithmic design for infinite-dimensional fun…
Multi-Marginal Schrödinger Bridge Matching
Byoungwoo Park, Juho Lee
Understanding the continuous evolution of populations from discrete temporal snapshots is a critical research challenge, particularly in fields like developmental biology and syste…
Improving Constrained Language Generation via Self-Distilled Twisted Sequential Monte Carlo
Sooyeon Kim, Giung Nam, Byoungwoo Park +1
Recent work has framed constrained text generation with autoregressive language models as a probabilistic inference problem. Among these, Zhao et al. (2024) introduced a promising…
Stochastic Optimal Control for Continuous-Time fMRI Representation Learning
Joonhyeong Park, Byoungwoo Park, Chang-Bae Bang +4
Learning robust representations from functional magnetic resonance imaging (fMRI) is fundamentally challenged by the temporal irregularity and noise inherent in data from heterogen…
Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series
Byoungwoo Park, Hyungi Lee, Juho Lee
Many real-world datasets, such as healthcare, climate, and economics, are often collected as irregular time series, which poses challenges for accurate modeling. In this paper, we…
Stochastic Optimal Control for Diffusion Bridges in Function Spaces
Byoungwoo Park, Jungwon Choi, Sungbin Lim +1
Recent advancements in diffusion models and diffusion bridges primarily focus on finite-dimensional spaces, yet many real-world problems necessitate operations in infinite-dimensio…