TurboFreeze / sghmcLinks
Stochastic Gradient Hamiltonian Monte Carlo
☆13Updated 5 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☆55Updated last year
- The code in this repository follows the paper "Stochastic gradient MCMC"☆26Updated 6 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- SAASBO: a package for high-dimensional bayesian optimization☆45Updated 3 years ago
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆49Updated last month
- Deep GPs built on top of TensorFlow/Keras and GPflow☆127Updated 10 months ago
- Heterogeneous Multi-output Gaussian Processes☆53Updated 5 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆150Updated 6 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 5 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Skew Gaussian Processes by Alessio Benavoli, Dario Azzimonti and Dario Piga☆16Updated last month
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- ☆152Updated 2 years ago
- Normalizing Flows with a resampled base distribution☆47Updated 3 years ago
- Sequential Neural Likelihood☆40Updated 6 years ago
- A tutorial for the 2018 paper Accurate Uncertainties for Deep Learning Using Calibrated Regression by Kuleshov et al.☆52Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Bayesian Optimisation over Multiple Continuous and Categorical Inputs (CoCaBO)☆51Updated 6 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- A meta repository pointing to the other repositories where the implementation of the supplementary examples for our tutorial "Hands-on Ba…☆134Updated 3 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆36Updated 4 years ago
- Implementation of the Gaussian Process Autoregressive Regression Model☆67Updated 7 months ago
- Multi-Output Gaussian Process Toolkit☆176Updated 3 months ago
- Variational Gaussian Process State-Space Models☆24Updated 9 years ago
- Nonparametric Differential Equation Modeling☆54Updated last year