kasparmartens / NeuralProcesses
Neural Processes implementation for 1D regression
☆65Updated 6 years ago
Alternatives and similar repositories for NeuralProcesses:
Users that are interested in NeuralProcesses are comparing it to the libraries listed below
- Convolutional Gaussian processes based on GPflow.☆96Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆40Updated 8 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- Deep Gaussian Processes with Doubly Stochastic Variational Inference☆149Updated 6 years ago
- Variational Fourier Features☆84Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆82Updated 4 years ago
- ☆40Updated 5 years ago
- see https://github.com/thangbui/geepee for a faster implementation☆37Updated 7 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 years ago
- Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.☆249Updated 7 months ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- We use a modified neural network instead of Gaussian process for Bayesian optimization.☆108Updated 7 years ago
- ☆37Updated 5 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Updated 9 years ago
- Deep Gaussian Processes in matlab☆91Updated 3 years ago
- ☆28Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆53Updated 5 months ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Repo for a paper about constructing priors on very deep models.☆72Updated 8 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 6 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆48Updated 6 years ago
- code release for the NIPS 2016 paper☆26Updated 8 years ago