ebonilla / gaussianprocessesLinks
Modern Gaussian Processes: Scalable Inference and Novel Applications
☆20Updated 6 years ago
Alternatives and similar repositories for gaussianprocesses
Users that are interested in gaussianprocesses are comparing it to the libraries listed below
Sorting:
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 4 months ago
- Non-Parametric Calibration for Classification (AISTATS 2020)☆19Updated 3 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- Implementation of the Convolutional Conditional Neural Process☆125Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- ☆37Updated 5 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Learning error bars for neural network predictions☆71Updated 5 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆35Updated 3 years ago
- Code for our ICML '19 paper: Neural Network Attributions: A Causal Perspective.☆51Updated 3 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 6 years ago
- Code for the ICML 2019 paper: Distribution Calibration for Regression☆22Updated 2 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".☆25Updated 2 years ago
- The code for Meta Learning for SGMCMC☆25Updated 6 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆77Updated 2 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 5 years ago