yliess86 / BayeFormersLinks
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.
☆45Updated 4 years ago
Alternatives and similar repositories for BayeFormers
Users that are interested in BayeFormers are comparing it to the libraries listed below
Sorting:
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Code for experiments to learn uncertainty☆30Updated 2 years ago
- This repository contains an official implementation of LPBNN.☆38Updated 2 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".☆113Updated 3 years ago
- Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.☆31Updated 4 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆272Updated 3 years ago
- Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, …☆86Updated 2 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆27Updated 2 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆55Updated 2 years ago
- ☆41Updated 5 years ago
- An official PyTorch implementation of "Regression Prior Networks" for effective runtime uncertainty estimation.☆36Updated 4 years ago
- ☆66Updated 5 years ago
- Work on Evidential Deep Learning to Quantify Classification Uncertainty☆60Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆89Updated 5 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆144Updated 2 years ago
- Quantile risk minimization☆24Updated last year
- Last-layer Laplace approximation code examples☆84Updated 3 years ago
- ☆42Updated 6 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆75Updated 4 years ago
- Code for Neural Manifold Clustering and Embedding☆61Updated 3 years ago
- Official implementation of the paper "Topographic VAEs learn Equivariant Capsules"☆80Updated 3 years ago
- Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).☆101Updated 3 months ago
- Ladder Variational Autoencoders (LVAE) in PyTorch☆92Updated 5 years ago
- Repository for Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification (NeurIPS 2024)☆43Updated 9 months ago
- Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"☆36Updated last year
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆20Updated 3 years ago
- ☆32Updated 3 years ago
- This repository is the code for Predictive Uncertainty Estimation using Deep Ensemble☆157Updated 3 years ago