teddykoker / evidential-learning-pytorchLinks
Evidential Deep Learning in PyTorch
☆64Updated 3 years ago
Alternatives and similar repositories for evidential-learning-pytorch
Users that are interested in evidential-learning-pytorch are comparing it to the libraries listed below
Sorting:
- [ICML 2023] Offical implementation of the paper "Uncertainty Estimation by Fisher Information-based Evidential Deep Learning".☆43Updated 2 years ago
- Official implementation of Evidential Uncertainty Quantification: A Variance-Based Perspective [WACV 2024]☆19Updated 2 months ago
- Supplementary material to reproduce "Multivariate Deep Evidential Regression"☆20Updated 3 years ago
- [ICLR 2023 Spotlight] Code release for "Dirichlet-based Uncertainty Calibration for Active Domain Adaptation"☆36Updated 2 years ago
- Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022☆19Updated 3 years ago
- An implementation of the state-of-the-art Deep Active Learning algorithms☆105Updated 2 years ago
- C-Mixup for NeurIPS 2022☆73Updated last year
- Supplementary material to reproduce "The Unreasonable Effectiveness of Deep Evidential Regression"☆29Updated 2 years ago
- Code for paper Trustworthy Multimodal Regression with Mixture of Normal-inverse Gamma Distributions.☆47Updated 2 years ago
- ☆109Updated 4 years ago
- Implementation of Deep evidential regression paper☆57Updated 4 years ago
- Repository for "Uncertainty Regularized Evidential Regression" published in AAAI 2024☆20Updated last year
- A curated publication list on evidential deep learning.☆141Updated 6 months ago
- Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty☆145Updated 2 years ago
- Active Test-Time Adaptation: Theoretical Analyses and An Algorithm [ICLR 2024]☆23Updated 11 months ago
- AAAI 2023: Semi-Supervised Deep Regression with Uncertainty Consistency and Variational Model Ensembling via Bayesian Neural Networks☆31Updated 2 years ago
- Implementation of "Evidential Deep Learning to Quantify Classification Uncertainty" proposing a method to quantify uncertainty in a neura…☆29Updated 2 years ago
- ☆17Updated last year
- [NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization☆30Updated 5 months ago
- This repo provides the codebase for "A General Framework for Weak Supervision"☆40Updated last year
- C-GMVAE: Gaussian Mixture VAE with Contrastive Learning for Multi-Label Classification☆57Updated 2 years ago
- Paper Reproduce for "Predictive Uncertainty Estimation via Prior Networks" by Andrey Malinin and Mark Gales.☆30Updated 5 years ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆53Updated last year
- [ICML 2024] Official code for Uncertainty Estimation by Density Aware Evidential Deep Learning☆13Updated last year
- Look-Ahead Data Acquisition via Augmentation for Deep Active Learning (NeurIPS 2021)☆15Updated last year
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 years ago
- Official Implementation of "Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions" (ICLR, …☆87Updated 2 years ago
- Latent Discriminant deterministic Uncertainty [ECCV2022]☆42Updated 3 years ago
- Multidimensional Uncertainty-Aware Evidential Neural Networks ( AAAI2021)☆16Updated 4 years ago
- Official implementation for "Partial and Asymmetric Contrastive Learning for Out-of-Distribution Detection in Long-Tailed Recognition" (I…☆43Updated 2 years ago