PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
torch.nn.Module
).pip install git+https://github.com/AdamCobb/hamiltorch
There are currently two blog posts that describe how to use hamiltorch
:
There are also notebook-style tutorials:
torch.nn.Module
(basic)
Please consider citing the following papers if you use hamiltorch
in your research:
For symmetric splitting:
@article{cobb2020scaling,
title={Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting},
author={Cobb, Adam D and Jalaian, Brian},
journal={Uncertainty in Artificial Intelligence},
year={2021}
}
For RMHMC:
@article{cobb2019introducing,
title={Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo},
author={Cobb, Adam D and Baydin, At{\i}l{\i}m G{\"u}ne{\c{s}} and Markham, Andrew and Roberts, Stephen J},
journal={arXiv preprint arXiv:1910.06243},
year={2019}
}