Alternatives and similar repositories for deep_evidential_regression_loss_pytorch

Users that are interested in deep_evidential_regression_loss_pytorch are comparing it to the libraries listed below

• hurrialice / uncertainties
  AM207 project: dissect aleatoric and epistemic uncertainty
  ☆90Updated 5 years ago
• hmi88 / what
  Pytorch implementation of "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?"
  ☆168Updated 6 years ago
• atilberk / evidential-deep-learning-to-quantify-classification-uncertainty
  Work on Evidential Deep Learning to Quantify Classification Uncertainty
  ☆60Updated 6 years ago
• avitase / mder
  Supplementary material to reproduce "Multivariate Deep Evidential Regression"
  ☆20Updated 3 years ago
• ShellingFord221 / My-implementation-of-What-Uncertainties-Do-We-Need-in-Bayesian-Deep-Learning-for-Computer-Vision
  Pytorch implementation of classification task in What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision (simple vers…
  ☆79Updated 4 years ago
• sharpenb / Posterior-Network
  Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)
  ☆78Updated 3 years ago
• pmorerio / dl-uncertainty
  "What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?", NIPS 2017 (unofficial code).
  ☆209Updated 5 years ago
• Jiachen-T-Wang / dirichlet-priornet
  Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.
  ☆30Updated 5 years ago
• danruod / IEDL
  [ICML 2023] Offical implementation of the paper "Uncertainty Estimation by Fisher Information-based Evidential Deep Learning".
  ☆43Updated 2 years ago
• KaosEngineer / PriorNetworks
  ☆66Updated 5 years ago
• y0ast / deterministic-uncertainty-quantification
  Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"
  ☆272Updated 3 years ago
• teddykoker / evidential-learning-pytorch
  Evidential Deep Learning in PyTorch
  ☆64Updated 3 years ago
• omegafragger / DDU
  Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
  ☆145Updated 2 years ago
• huyng / incertae
  Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
  ☆70Updated 5 years ago
• KaosEngineer / PriorNetworks-OLD
  ☆42Updated 6 years ago
• ENSTA-U2IS-AI / LDU
  Latent Discriminant deterministic Uncertainty [ECCV2022]
  ☆42Updated 3 years ago
• mattiasegu / uncertainty_estimation_deep_learning
  This repository provides the code used to implement the framework to provide deep learning models with total uncertainty estimates as des…
  ☆228Updated last year
• giannifranchi / LP_BNN
  This repository contains an official implementation of LPBNN.
  ☆38Updated 2 years ago
• TUM-DAML / dbu-robustness
  Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)
  ☆28Updated 2 years ago
• deargen / MT-ENet
  Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022
  ☆19Updated 3 years ago
• JakobCode / UncertaintyInNeuralNetworks_Resources
  ☆109Updated 4 years ago
• sungyubkim / MCDO
  A pytorch implementation of MCDO(Monte-Carlo Dropout methods)
  ☆57Updated 6 years ago
• cpark321 / uncertainty-deep-learning
  ☆239Updated 5 years ago
• yliess86 / BayeFormers
  General API for Deep Bayesian Variational Inference by Backpropagation. The repository has been designed to work with Transformers like a…
  ☆45Updated 5 years ago
• kobybibas / pnml_ood_detection
  Out-of-distribution detection using the pNML regret. NeurIPS2021
  ☆25Updated 10 months ago
• AMLab-Amsterdam / DIVA
  Implementation of 'DIVA: Domain Invariant Variational Autoencoders'
  ☆105Updated 5 years ago
• TsungWeiTsai / MiCE
  Pytorch implementation for ICLR 2021 paper - MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering
  ☆52Updated 4 years ago
• belaalb / G2DM
  Generalizing to unseen domains via distribution matching
  ☆72Updated 5 years ago
• pasteurlabs / unreasonable_effective_der
  Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"
  ☆29Updated 2 years ago
• IntelLabs / AVUC
  Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.
  ☆55Updated 2 years ago