aleximmer / BNN-predictionsLinks
Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
☆16Updated 2 years ago
Alternatives and similar repositories for BNN-predictions
Users that are interested in BNN-predictions are comparing it to the libraries listed below
Sorting:
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆20Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆32Updated 3 months ago
- ☆152Updated 2 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".☆25Updated 2 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 4 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last month
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- ☆15Updated 2 years ago
- Bayesian neural network package☆148Updated 4 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆85Updated 4 years ago
- Simple (and cheap!) neural network uncertainty estimation☆66Updated last month
- Bayesian Optimization with Density-Ratio Estimation☆23Updated 2 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Robust initialisation of inducing points in sparse variational GP regression models.☆33Updated 2 years ago
- Repo for the Tutorials of Day1-Day2 of the Nordic Probabilistic AI School 2023☆17Updated 2 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆53Updated last year
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- 🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0☆26Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆42Updated 11 months ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Regression datasets from the UCI repository with standardized test-train splits.☆47Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- [NeurIPS 2020] Task-Agnostic Amortized Inference of Gaussian Process Hyperparameters (AHGP)☆22Updated 4 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆223Updated last year
- Example code of Sparse Gaussian Process Attention (ICLR 2023)☆24Updated last year