PGM-Lab / PAC2BAYESLinks
This repository contains the Python code to reproduce all the figures and experiments presented in the paper: Masegosa, Andrés. R., Learning under Model Misspecification: Applications to Variational and Ensemble methods.
☆9Updated 2 years ago
Alternatives and similar repositories for PAC2BAYES
Users that are interested in PAC2BAYES are comparing it to the libraries listed below
Sorting:
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆84Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- A tensorflow implementation of VAE training with Renyi divergence☆31Updated 8 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- code release for the NIPS 2016 paper☆27Updated 8 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated 2 years ago
- PAC-Bayes with Backprop - Tighter risk certificates for neural networks☆24Updated 3 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆71Updated 8 years ago
- Natural Gradient, Variational Inference☆29Updated 5 years ago
- ☆53Updated 10 months ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Code for "Inference Suboptimality in Variational Autoencoders"☆14Updated 5 years ago
- ☆28Updated 3 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 7 months ago
- ☆40Updated 6 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆39Updated 6 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 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
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Gaussian processes with PyTorch☆30Updated 3 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 6 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago