5 papers
Distributionally Robust Schrödinger Bridge
Jinhwan Sul, Panagiotis Theodoropoulos, Vincent Pacelli +2
Schrödinger bridge (SB) learns stochastic transport between prescribed initial and target distributions. When the initial distribution shifts at test time, the learned dynamics can…
Reinforcement Learning to Accelerate Primal-Dual Hybrid Gradient for Linear Programming
Jinhwan Sul, Alex Oshin, Evangelos A. Theodorou
Primal-dual hybrid gradient (PDHG) methods solve large-scale linear programs (LPs) using GPU-friendly matrix-vector products and projections, but their practical performance depend…
Efficient Generative Modeling beyond Memoryless Diffusion via Adjoint Schrödinger Bridge Matching
Jeongwoo Shin, Jinhwan Sul, Joonseok Lee +3
Diffusion models often yield highly curved trajectories and noisy score targets due to an uninformative, memoryless forward process that induces independent data-noise coupling. We…
SummDiff: Generative Modeling of Video Summarization with Diffusion
Kwanseok Kim, Jaehoon Hahm, Sumin Kim +3
Video summarization is a task of shortening a video by choosing a subset of frames while preserving its essential moments. Despite the innate subjectivity of the task, previous wor…
Generic and Scalable Differential Equation Solver for Quantum Scientific Computing
Jinhwan Sul, Yan Wang
One of the most important topics in quantum scientific computing is solving differential equations. In this paper, generalized quantum functional expansion (QFE) framework is propo…