stanislavfort / exploring_the_limits_of_OOD_detection
Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanislav Fort, Jie Ren, Balaji Lakshminarayanan, published at NeurIPS 2021.
☆43Updated 3 years ago
Alternatives and similar repositories for exploring_the_limits_of_OOD_detection:
Users that are interested in exploring_the_limits_of_OOD_detection are comparing it to the libraries listed below
- ☆46Updated 4 years ago
- MOS: Towards Scaling Out-of-distribution Detection for Large Semantic Space☆91Updated 3 years ago
- This is a code repository for paper OODformer: Out-Of-Distribution Detection Transformer☆40Updated 3 years ago
- Robust Out-of-distribution Detection in Neural Networks☆72Updated 2 years ago
- [SafeAI'21] Feature Space Singularity for Out-of-Distribution Detection.☆80Updated 4 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆119Updated 3 years ago
- [ICML 2021] “ Self-Damaging Contrastive Learning”, Ziyu Jiang, Tianlong Chen, Bobak Mortazavi, Zhangyang Wang☆63Updated 3 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆55Updated 2 years ago
- (NeurIPS 2020 Workshop on SSL) Official Implementation of "MixCo: Mix-up Contrastive Learning for Visual Representation"☆58Updated 2 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆85Updated 2 years ago
- Code for NeurIPS 2021 paper "ReAct: Out-of-distribution Detection With Rectified Activations"☆52Updated 3 years ago
- The repository for the official Biased Action Recognition (BAR) dataset for the paper Learning from Failure: Training Debiased Classifier…☆30Updated 4 years ago
- ☆58Updated 3 years ago
- Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.☆134Updated last year
- Official codebase of the "Rehearsal revealed:The limits and merits of revisiting samples in continual learning" paper.☆27Updated 3 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆90Updated 4 years ago
- We propose a theoretically motivated method, Adversarial Training with informative Outlier Mining (ATOM), which improves the robustness o…☆57Updated 3 years ago
- Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)☆103Updated 3 years ago
- Confidence-Aware Learning for Deep Neural Networks (ICML2020)☆74Updated 4 years ago
- Codebase for the paper titled "Continual learning with local module selection"☆25Updated 3 years ago
- Generalizing to unseen domains via distribution matching☆70Updated 4 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆104Updated 4 years ago
- MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)☆109Updated 2 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 3 years ago
- ☆108Updated last year
- Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training wi…☆52Updated 3 years ago
- Repo for the paper: "Agree to Disagree: Diversity through Disagreement for Better Transferability"☆35Updated 2 years ago
- Code release for paper Extremely Simple Activation Shaping for Out-of-Distribution Detection☆52Updated 6 months ago
- Continual Learning in Low-rank Orthogonal Subspaces (NeurIPS'20)☆36Updated 4 years ago