AdamCobb / hamiltorch
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
☆428Updated 4 months ago
Alternatives and similar repositories for hamiltorch:
Users that are interested in hamiltorch are comparing it to the libraries listed below
- Laplace approximations for Deep Learning.☆483Updated last month
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆302Updated last month
- ☆147Updated 2 years ago
- Manifold-learning flows (ℳ-flows)☆229Updated 4 years ago
- Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.☆423Updated last year
- ☆235Updated 2 years ago
- Gaussian processes in JAX.☆473Updated last month
- Constrained optimization toolkit for PyTorch☆664Updated 2 years ago
- Gaussian process modelling in Python☆220Updated last month
- BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.☆568Updated 2 weeks ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆273Updated 3 years ago
- Normalizing flows in PyTorch☆352Updated last month
- Normalizing flows in PyTorch☆869Updated 3 weeks ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆561Updated last week
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆232Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆169Updated 2 years ago
- A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods☆1,426Updated 8 months ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆286Updated 3 years ago
- Optimal transport tools implemented with the JAX framework, to get differentiable, parallel and jit-able computations.☆555Updated 2 weeks ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆110Updated this week
- PyTorch implementation of bayesian neural network [torchbnn]☆505Updated 5 months ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆456Updated last year
- Uncertainty quantification with PyTorch☆333Updated 2 months ago
- State Space Models library in JAX☆726Updated last month
- Deep GPs built on top of TensorFlow/Keras and GPflow☆122Updated 3 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆99Updated this week
- Probabilistic Numerics in Python.☆447Updated 8 months ago
- Simulation-based inference toolkit☆616Updated this week
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Implementation of normalizing flows in TensorFlow 2 including a small tutorial.☆146Updated 4 months ago