A Tensor Network Approach to Finite Markov Decision Processes. - Edward Gillman; Dominic C. Rose; Juan P. Garrahan (CoRR, 2020)

A reinforcement learning approach to rare trajectory sampling. - Dominic C. Rose; Jamie F. Mair; Juan P. Garrahan (CoRR, 2020)

A deep learning functional estimator of optimal dynamics for sampling large deviations. - Tom H. E. Oakes; Adam Moss; Juan P. Garrahan (Mach. Learn. Sci. Technol., 2020)

Reinforcement learning of rare diffusive dynamics. - Avishek Das; Dominic C. Rose; Juan P. Garrahan; David T. Limmer (CoRR, 2021)

Training neural network ensembles via trajectory sampling. - Jamie F. Mair; Dominic C. Rose; Juan P. Garrahan (CoRR, 2022)

Reinforcement Learning with Tensor Networks: Application to Dynamical Large Deviations. - Edward Gillman; Dominic C. Rose; Juan P. Garrahan (CoRR, 2022)

Minibatch training of neural network ensembles via trajectory sampling. - Jamie F. Mair; Luke Causer; Juan P. Garrahan (CoRR, 2023)

Discrete generative diffusion models without stochastic differential equations: a tensor network approach. - Luke Causer; Grant M. Rotskoff; Juan P. Garrahan (CoRR, 2024)