3 papers
cs.LG2025
Identifiable learning of dissipative dynamics
Aiqing Zhu, Beatrice W. Soh, Grigorios A. Pavliotis +1
Complex dissipative systems appear across science and engineering, from polymers and active matter to learning algorithms. These systems operate far from equilibrium, where energy…
cs.LG2025
Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
Aiqing Zhu, Yuting Pan, Qianxiao Li
Continuous dynamical systems are cornerstones of many scientific and engineering disciplines. While machine learning offers powerful tools to model these systems from trajectory da…
cs.LG2024
DynGMA: a robust approach for learning stochastic differential equations from data
Aiqing Zhu, Qianxiao Li
Learning unknown stochastic differential equations (SDEs) from observed data is a significant and challenging task with applications in various fields. Current approaches often use…