matthewwicker / deepbayesLinks
Optimizers for performing approximate Bayesian inference on neural network parameters with Tensorflow and JAX
☆13Updated last year
Alternatives and similar repositories for deepbayes
Users that are interested in deepbayes are comparing it to the libraries listed below
Sorting:
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆21Updated 3 years ago
- simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…☆15Updated 5 years ago
- ☆52Updated 2 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆75Updated 3 years ago
- Algorithms for computations on random manifolds made easier☆94Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆146Updated 3 weeks ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Refining continuous-in-depth neural networks☆42Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Re-implementation of Hamiltonian Generative Networks paper☆33Updated 3 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆39Updated 4 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆23Updated 5 years ago
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- Supplementary code for the NeurIPS 2020 paper "Matern Gaussian processes on Riemannian manifolds".☆29Updated 10 months ago
- Code repo for "Function-Space Distributions over Kernels"☆32Updated 4 years ago
- ☆25Updated 2 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 7 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆64Updated last year
- ☆37Updated 5 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Bayesian algorithm execution (BAX)☆55Updated 4 years ago
- Nonparametric Differential Equation Modeling☆56Updated last year
- ☆155Updated 3 years ago
- ☆54Updated last year
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 4 years ago
- ☆15Updated 3 years ago
- Neural likelihood-free methods in PyTorch.☆39Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆49Updated 5 years ago