Software
Recent Papers:
JaxSGMC: Modular stochastic gradient MCMC in JAX
S. Thaler, P. Fuchs, A. Cukarska, J. Zavadlav, SoftwareX 2024, paper
An application-agnostic library for stochastic gradient Markov chain Monte Carlo (SG-MCMC) in JAX, enabling Bayesian deep learning.
Published code:
Relative Entropy Minimization
Code for training of coarse-grained molecular models with relative entropy minimization.
Jax / Haiku implementation of DimeNet++
This DimeNet++ implementation can be used for molecular dynamics simulations with Jax, M.D. and for molecular property prediction.