activity
20172025
most citedDeep Learning Theory Review: An Optimal Control and Dynamical Systems Perspective

47 citations · 54 across the 10 of their papers we have counts for

collaborators

12 papers

cs.LG2025

Optimal Control Theoretic Neural Optimizer: From Backpropagation to Dynamic Programming

Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou

Optimization of deep neural networks (DNNs) has been a driving force in the advancement of modern machine learning and artificial intelligence. With DNNs characterized by a prolong…

stat.ML2025

Momentum Multi-Marginal Schrödinger Bridge Matching

Panagiotis Theodoropoulos, Augustinos D. Saravanos, Evangelos A. Theodorou +1

Understanding complex systems by inferring trajectories from sparse sample snapshots is a fundamental challenge in a wide range of domains, e.g., single-cell biology, meteorology,…

stat.ML2024

Deep Generalized Schrödinger Bridges: From Image Generation to Solving Mean-Field Games

Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou

Generalized Schrödinger Bridges (GSBs) are a fundamental mathematical framework used to analyze the most likely particle evolution based on the principle of least action including…

stat.ML2024

Feedback Schrödinger Bridge Matching

Panagiotis Theodoropoulos, Nikolaos Komianos, Vincent Pacelli +2

Recent advancements in diffusion bridges for distribution transport problems have heavily relied on matching frameworks, yet existing methods often face a trade-off between scalabi…

stat.ML20221 cited

Deep Generalized Schrödinger Bridge

Guan-Horng Liu, Tianrong Chen, Oswin So +1

Mean-Field Game (MFG) serves as a crucial mathematical framework in modeling the collective behavior of individual agents interacting stochastically with a large population. In thi…

cs.LG20212 cited

Second-Order Neural ODE Optimizer

Guan-Horng Liu, Tianrong Chen, Evangelos A. Theodorou

We propose a novel second-order optimization framework for training the emerging deep continuous-time models, specifically the Neural Ordinary Differential Equations (Neural ODEs).…