cambridge-mlg / sghmc_dgp
☆28Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for sghmc_dgp
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Heterogeneous Multi-output Gaussian Processes☆51Updated 4 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆147Updated 5 years ago
- ☆40Updated 5 years ago
- A collection of Gaussian process models☆30Updated 7 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated 9 months ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- Variational Fourier Features☆83Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Library for Deep Gaussian Processes based on GPflow☆19Updated 4 years ago
- A community repository for benchmarking Bayesian methods☆109Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆64Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆81Updated 5 months ago
- Continual Gaussian Processes☆31Updated last year
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Python and MATLAB code for Stein Variational sampling methods☆23Updated 5 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 5 years ago
- Deep Gaussian Processes in Python☆232Updated 3 years ago
- Convolutional Gaussian processes based on GPflow.☆95Updated 7 years ago
- Deep Gaussian Processes in matlab☆90Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Neural Processes implementation for 1D regression☆65Updated 5 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated last year
- Implementation of stochastic variational inference for differentially deep gaussian processes☆15Updated 6 years ago
- Python library for Recurrent Gaussian Processes☆19Updated 7 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago