TurboFreeze / sghmcLinks
Stochastic Gradient Hamiltonian Monte Carlo
☆12Updated 6 years ago
Alternatives and similar repositories for sghmc
Users that are interested in sghmc are comparing it to the libraries listed below
Sorting:
- Bayesian Neural Network Surrogates for Bayesian Optimization☆63Updated last year
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 5 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Library for Deep Gaussian Processes based on GPflow☆19Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆111Updated 3 years ago
- The code in this repository follows the paper "Stochastic gradient MCMC"☆26Updated 6 years ago
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- SAASBO: a package for high-dimensional bayesian optimization☆47Updated 4 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆37Updated 4 years ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆51Updated 3 months ago
- Heterogeneous Multi-output Gaussian Processes☆54Updated 5 years ago
- Cost-aware Bayesian optimization via the Pandora's box Gittins index☆13Updated 3 months ago
- Sequential Neural Likelihood☆42Updated 6 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Skew Gaussian Processes by Alessio Benavoli, Dario Azzimonti and Dario Piga☆16Updated 3 months ago
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated last year
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆151Updated 6 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆155Updated 3 years ago
- Implementations of Normalizing Flows in Pytorch/Pyro☆18Updated 5 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- Python and MATLAB code for Stein Variational sampling methods☆26Updated 6 years ago
- Implementation for Non-stationary Spectral Kernels (NIPS 2017)☆20Updated 5 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 3 years ago
- Deep Gaussian Processes in Python☆236Updated 4 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆68Updated 9 months ago
- Variational Gaussian Process State-Space Models☆25Updated 10 years ago