3 papers
cs.LG2026
One-Sided Quantile Coupling for Flow Matching
Jin-Young Kim, So-Yoon Cho, Hyun-Gyoon Kim
Flow Matching trains continuous-time generative models by regressing the velocity field of a probability path between a simple source distribution and a target data distribution. T…
cs.CE2026
Diffolio: A Diffusion Model for Multivariate Probabilistic Financial Time-Series Forecasting and Portfolio Construction
So-Yoon Cho, Jin-Young Kim, Kayoung Ban +2
Probabilistic forecasting is crucial in multivariate financial time-series for constructing efficient portfolios that account for complex cross-sectional dependencies. In this pape…
cs.CV2025
Denoising Task Difficulty-based Curriculum for Training Diffusion Models
Jin-Young Kim, Hyojun Go, Soonwoo Kwon +1
Diffusion-based generative models have emerged as powerful tools in the realm of generative modeling. Despite extensive research on denoising across various timesteps and noise lev…