fbickfordsmith / epigLinks
Bayesian active learning with EPIG data acquisition
☆32Updated 2 months ago
Alternatives and similar repositories for epig
Users that are interested in epig are comparing it to the libraries listed below
Sorting:
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 weeks ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- Simple (and cheap!) neural network uncertainty estimation☆66Updated last month
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021☆16Updated 2 years ago
- Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design☆34Updated 4 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆10Updated 2 years ago
- ☆15Updated 2 years ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- PyTorch implementation of Stein Variational Gradient Descent☆45Updated 2 years ago
- ☆18Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆77Updated 3 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 3 years ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆20Updated 3 years ago
- ☆54Updated 11 months ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- ☆25Updated last year
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆24Updated 2 years ago
- Large-scale uncertainty benchmark in deep learning.☆60Updated last month
- ☆152Updated 2 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆51Updated last year
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆48Updated last week