mtitsias / gadMCMCLinks
Gradient-based Adaptive Markov chain Monte Carlo
☆31Updated 6 years ago
Alternatives and similar repositories for gadMCMC
Users that are interested in gadMCMC are comparing it to the libraries listed below
Sorting:
- Max-value Entropy Search for Efficient Bayesian Optimization☆80Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
- Code for ICML 2019 paper on "Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations"☆19Updated 5 years ago
- Code for An Adaptive Empirical Bayesian Method for Sparse Deep Learning (NeurIPS'19)☆20Updated 4 years ago
- Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)☆22Updated 6 years ago
- ☆29Updated 6 years ago
- Riemannian stochastic optimization algorithms: Version 1.0.3☆67Updated 3 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 6 years ago
- Demo implementation of Learning Koopman Invariant Subspaces for Dynamic Mode Decomposition☆40Updated 3 years ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆122Updated 6 years ago
- Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…☆26Updated 11 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"☆26Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated last year
- Optimization using Stochastic quasi-Newton methods☆42Updated 8 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Code to produce demos of Metroplis-Hastings and Hamiltonian Monte Carlo samplers.☆36Updated 11 years ago
- A variational method for fast, approximate inference for stochastic differential equations.☆45Updated 7 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆410Updated last year
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 3 years ago
- ☆47Updated 5 years ago
- Stochastic Optimization for Optimal Transport☆22Updated 9 years ago
- Deep neural network kernel for Gaussian process☆212Updated 5 years ago
- Adaptive Regularized Newton Method for Riemannian Optimization☆32Updated 6 years ago
- Code for Randomly Projected Additive Gaussian Processes☆25Updated 5 years ago
- LIBS2ML: A Library for Scalable Second Order Machine Learning Algorithms☆12Updated 4 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆125Updated 7 years ago
- Gaussian processes with PyTorch☆30Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago