Sanaelotfi / Bayesian_model_comparison
Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".
☆35Updated 2 years ago
Alternatives and similar repositories for Bayesian_model_comparison
Users that are interested in Bayesian_model_comparison are comparing it to the libraries listed below
Sorting:
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated 2 years ago
- ☆53Updated 9 months ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Pytorch code for "Improving Self-Supervised Learning by Characterizing Idealized Representations"☆41Updated 2 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
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods☆19Updated 3 years ago
- ☆30Updated 4 years ago
- Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"☆22Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆76Updated last year
- ☆21Updated 3 years ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆35Updated last year
- Bayesian active learning with EPIG data acquisition☆31Updated 3 weeks ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- Last-layer Laplace approximation code examples☆83Updated 3 years ago
- Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.☆33Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 3 years ago
- ☆32Updated 2 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 4 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 4 years ago
- ☆15Updated 2 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Stochastic Gradient Langevin Dynamics for Bayesian learning☆31Updated 3 years ago
- Code associated with our paper "Learning Group Structure and Disentangled Representations of Dynamical Environments"☆15Updated 2 years ago
- ☆18Updated last year