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).
## How to install
pip install git+https://github.com/AdamCobb/hamiltorch
## How does it work?
There are currently two blog posts that describe how to use
hamiltorch:
There are also notebook-style tutorials:
torch.nn.Module(basic)
## How to cite?
Please consider citing the following papers if you use
hamiltorchin 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={arXiv preprint arXiv:2010.06772}, year={2020} }
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} }
## Who developed hamiltorch?