atilberk / evidential-deep-learning-to-quantify-classification-uncertainty
Work on Evidential Deep Learning to Quantify Classification Uncertainty
☆59Updated 6 years ago
Alternatives and similar repositories for evidential-deep-learning-to-quantify-classification-uncertainty:
Users that are interested in evidential-deep-learning-to-quantify-classification-uncertainty are comparing it to the libraries listed below
- ☆40Updated 5 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆56Updated 6 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆55Updated 2 years ago
- ☆66Updated 5 years ago
- Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)☆28Updated 2 years ago
- Implementation of Deep evidential regression paper☆53Updated 4 years ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆135Updated last year
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆74Updated 3 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆76Updated 2 years ago
- Official repository for the paper "Masksembles for Uncertainty Estimation" (CVPR 2021).☆101Updated last year
- Generalizing to unseen domains via distribution matching☆70Updated 4 years ago
- ☆34Updated 4 years ago
- ShellingFord221 / My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-VisionPytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple vers…☆78Updated 3 years ago
- General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…☆42Updated 4 years ago
- Code for experiments to learn uncertainty☆30Updated last year
- Robust Out-of-distribution Detection in Neural Networks☆72Updated 2 years ago
- An implementation of the Residual Flow algorithm for out-of-distribution detection.☆30Updated 2 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆271Updated 2 years ago
- This repository contains an official implementation of LPBNN.☆39Updated last year
- ☆46Updated 4 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆85Updated 2 years ago
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆40Updated 3 years ago
- ☆53Updated 6 years ago
- Last-layer Laplace approximation code examples☆83Updated 3 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆55Updated 2 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆111Updated 2 years ago
- Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020☆49Updated 3 years ago
- Implementation of Bayesian Gradient Descent☆37Updated last year
- Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanis…☆43Updated 3 years ago
- ☆37Updated 5 years ago