ashafaei / OD-test
OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)
☆62Updated last year
Alternatives and similar repositories for OD-test:
Users that are interested in OD-test are comparing it to the libraries listed below
- Principled Detection of Out-of-Distribution Examples in Neural Networks☆201Updated 7 years ago
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- Training Confidence-Calibrated Classifier for Detecting Out-of-Distribution Samples / ICLR 2018☆181Updated 5 years ago
- Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"☆30Updated 5 years ago
- The Ultimate Reference for Out of Distribution Detection with Deep Neural Networks☆118Updated 5 years ago
- Outlier Exposure with Confidence Control for Out-of-Distribution Detection☆69Updated 4 years ago
- Gold Loss Correction☆87Updated 6 years ago
- ☆46Updated 4 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- ☆46Updated 2 years ago
- A DIRT-T Approach to Unsupervised Domain Adaptation (ICLR 2018)☆175Updated 7 years ago
- This repo provides code used in the paper "Predicting with High Correlation Features" (https://arxiv.org/abs/1910.00164):☆54Updated 5 years ago
- Overcoming Catastrophic Forgetting by Incremental Moment Matching (IMM)☆35Updated 7 years ago
- Robust Out-of-distribution Detection in Neural Networks☆72Updated 3 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Code for Piggyback: Adapting a Single Network to Multiple Tasks by Learning to Mask Weights☆182Updated 5 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 3 years ago
- ☆66Updated 5 years ago
- Release of CIFAR-10.1, a new test set for CIFAR-10.☆222Updated 5 years ago
- Robust loss functions for deep neural networks (CVPR 2017)☆91Updated 4 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- Self-Supervised Learning for OOD Detection (NeurIPS 2019)☆266Updated 3 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆86Updated 5 years ago
- A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks☆227Updated 6 years ago
- PyTorch Implementations of Dropout Variants☆87Updated 7 years ago
- Example code for the paper "Understanding deep learning requires rethinking generalization"☆178Updated 4 years ago
- Implementation of the variational continual learning method☆188Updated 5 years ago
- ☆87Updated 3 years ago
- Official Implementation of "Random Path Selection for Incremental Learning" paper. NeurIPS 2019☆53Updated 2 years ago