dilinwang820 / Stein-Variational-Gradient-Descent
code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
☆398Updated last year
Alternatives and similar repositories for Stein-Variational-Gradient-Descent:
Users that are interested in Stein-Variational-Gradient-Descent are comparing it to the libraries listed below
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Deep neural network kernel for Gaussian process☆202Updated 4 years ago
- Deep Gaussian Processes in Python☆233Updated 3 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- code for Structured Variational Autoencoders☆352Updated 6 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Structured Inference Networks for Nonlinear State Space Models☆268Updated 7 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Experiment code for Stochastic Gradient Hamiltonian Monte Carlo☆105Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Python package facilitating the use of Bayesian Deep Learning methods with Variational Inference for PyTorch☆359Updated 5 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 8 months ago
- Understanding normalizing flows☆132Updated 5 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆141Updated 9 years ago
- Pytorch implementation of Neural Processes for functions and images☆229Updated 3 years ago
- OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.☆93Updated 3 years ago
- ☆180Updated 5 years ago
- Kalman Variational Auto-Encoder☆135Updated 6 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆126Updated 6 years ago
- I am in [research] stepped in so far that, should I wade no more, Returning were as tedious as go o'er. -MacBeth☆184Updated 10 years ago
- Dropout As A Bayesian Approximation: Code☆201Updated 9 years ago
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- Masked Autoregressive Flow☆212Updated 8 months ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆233Updated 6 years ago
- Package implementing various parametric and nonparametric methods for conditional density estimation☆195Updated 2 years ago
- Neural Processes implementation for 1D regression☆65Updated 6 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 7 years ago
- Papers for Bayesian-NN☆322Updated 5 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago