20 citations · 20 across the 1 of their papers we have counts for
2 papers
physics.comp-ph2019★ 20 cited
Deep learning Markov and Koopman models with physical constraints
Andreas Mardt, Luca Pasquali, Frank Noé +1
The long-timescale behavior of complex dynamical systems can be described by linear Markov or Koopman models in a suitable latent space. Recent variational approaches allow the lat…
stat.ML2018
Deep Generative Markov State Models
Hao Wu, Andreas Mardt, Luca Pasquali +1
We propose a deep generative Markov State Model (DeepGenMSM) learning framework for inference of metastable dynamical systems and prediction of trajectories. After unsupervised tra…