JeremiasKnoblauch / GVIPublic
Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
☆18Updated 5 years ago
Related projects ⓘ
Alternatives and complementary repositories for GVIPublic
- Code for the paper "Bayesian Neural Network Priors Revisited"☆55Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆38Updated last year
- Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks☆9Updated 2 years ago
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆17Updated 2 years ago
- ☆15Updated 2 years ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆21Updated 2 years ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 3 years ago
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆23Updated last year
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- ☆52Updated 3 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
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- scipy linear operators for the Hessian, Fisher/GGN, and more in PyTorch☆18Updated 2 weeks ago
- Neural likelihood-free methods in PyTorch.☆39Updated 4 years ago
- Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models☆19Updated 2 years ago
- Repo for our paper "Repulsive deep ensembles are Bayesian"☆19Updated 2 years ago
- Euclidean Wasserstein-2 optimal transportation☆44Updated last year
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆21Updated last year
- Bayesian active learning with EPIG data acquisition