Juan P. Garrahan

According to our database, Juan P. Garrahan authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Discrete generative diffusion models without stochastic differential equations: a tensor network approach.

Luke Causer, Grant M. Rotskoff, Juan P. Garrahan

CoRR, 2024

2023

Minibatch training of neural network ensembles via trajectory sampling.

Jamie F. Mair, Luke Causer, Juan P. Garrahan

CoRR, 2023

2022

Reinforcement Learning with Tensor Networks: Application to Dynamical Large Deviations.

Edward Gillman, Dominic C. Rose, Juan P. Garrahan

CoRR, 2022

Training neural network ensembles via trajectory sampling.

Jamie F. Mair, Dominic C. Rose, Juan P. Garrahan

CoRR, 2022

2021

Reinforcement learning of rare diffusive dynamics.

Avishek Das, Dominic C. Rose, Juan P. Garrahan, David T. Limmer

CoRR, 2021

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

A reinforcement learning approach to rare trajectory sampling.

Dominic C. Rose, Jamie F. Mair, Juan P. Garrahan

CoRR, 2020

A Tensor Network Approach to Finite Markov Decision Processes.

Edward Gillman, Dominic C. Rose, Juan P. Garrahan

CoRR, 2020