yliess86 / BayeFormers
General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like architectures. Compatible with the HuggingFace Transformers models.
☆42Updated 4 years ago
Alternatives and similar repositories for BayeFormers:
Users that are interested in BayeFormers are comparing it to the libraries listed below
- Code for experiments to learn uncertainty☆30Updated last year
- This repository contains an official implementation of LPBNN.☆39Updated last year
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆110Updated 2 years ago
- Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.☆30Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆76Updated 2 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- ☆32Updated 2 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆72Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆22Updated last year
- beta-NLL introduced in our paper "On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks" ICLR 2022☆38Updated 2 years ago
- Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, …☆79Updated last year
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆131Updated last year
- Code for paper "Adversarial Support Alignment"☆22Updated 2 years ago
- Quantile risk minimization☆24Updated 6 months ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆51Updated 4 years ago
- Bayesian active learning with EPIG data acquisition☆27Updated last week
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆55Updated 2 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆27Updated 3 years ago
- Official code for the ICLR 2021 paper Neural ODE Processes☆70Updated 2 years ago
- Supporing code for the paper "Bayesian Model Selection, the Marginal Likelihood, and Generalization".☆35Updated 2 years ago
- Active and Sample-Efficient Model Evaluation☆24Updated 3 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆74Updated 3 years ago
- Official implementation of "How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?", TMLR 2023.☆18Updated 10 months ago
- Energy-Based Models for Continual Learning Official Repository (PyTorch)☆40Updated 2 years ago
- Training quantile models☆42Updated 2 months ago
- Implementation of Deep evidential regression paper☆53Updated 4 years ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆19Updated 2 years ago