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 Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆44Updated 4 months ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 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
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 5 years ago
- ☆37Updated 5 years ago
- The code for Meta Learning for SGMCMC☆25Updated 6 years ago
- ☆54Updated last year
- Implementation of the Convolutional Conditional Neural Process☆125Updated 4 years ago
- A library for uncertainty quantification based on PyTorch☆122Updated 3 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated 2 years ago
- Spatio-temporal alignements: Optimal transport in space and time☆47Updated 5 months ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆35Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Gaussian Process Prior Variational Autoencoder☆85Updated 6 years ago
- Probabilistic Auto-Encoder☆43Updated 2 years ago
- Code for "Variational Autoencoder with Learned Latent Structure"☆34Updated 4 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- A brief tutorial on the Wasserstein auto-encoder☆84Updated 6 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆20Updated 3 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago