BioroboticsLab / IBA
Information Bottlenecks for Attribution
☆77Updated 2 years ago
Alternatives and similar repositories for IBA:
Users that are interested in IBA are comparing it to the libraries listed below
- Official implementation of paper Gradient Matching for Domain Generalization☆119Updated 3 years ago
- Domain Generalization via Model-Agnostic Learning of Semantic Features☆147Updated last year
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- ☆24Updated 3 years ago
- Figures & code from the paper "Shortcut Learning in Deep Neural Networks" (Nature Machine Intelligence 2020)☆96Updated 2 years ago
- Code for the Paper "Restricting the Flow: Information Bottlenecks for Attribution"☆76Updated 4 years ago
- Original dataset release for CIFAR-10H☆82Updated 4 years ago
- ☆140Updated 4 years ago
- Crowdsourcing metrics and test datasets beyond ImageNet (ICML 2022 workshop)☆38Updated 9 months ago
- A pytorch implementation of our jacobian regularizer to encourage learning representations more robust to input perturbations.☆125Updated last year
- Natural Language Descriptions of Deep Visual Features, ICLR 2022☆62Updated last year
- ☆73Updated 4 years ago
- Winning Solution of the NeurIPS 2020 Competition on Predicting Generalization in Deep Learning☆38Updated 3 years ago
- A PyTorch converter for SimCLR checkpoints☆109Updated 4 years ago
- ☆32Updated 5 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 3 years ago
- Visual Representation Learning Benchmark for Self-Supervised Models☆35Updated 10 months ago
- Generalizing to unseen domains via distribution matching☆70Updated 4 years ago
- PyTorch Implementation - Mine Your Own vieW: Self-Supervised Learning Through Across-Sample Prediction☆31Updated 3 years ago
- A Disentangling Invertible Interpretation Network☆121Updated 3 years ago
- NeurIPS 2021 | Fine-Grained Neural Network Explanation by Identifying Input Features with Predictive Information☆32Updated 3 years ago
- Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)☆85Updated last month
- Code for CVPR2021 paper 'Where and What? Examining Interpretable Disentangled Representations'.☆43Updated 3 years ago
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data☆111Updated 4 years ago
- OD-test: A Less Biased Evaluation of Out-of-Distribution (Outlier) Detectors (PyTorch)☆62Updated last year
- [ICLR'21] Counterfactual Generative Networks☆107Updated 3 years ago
- ☆34Updated 3 years ago
- ☆36Updated 3 years ago
- An implementation of "A Simple Framework for Contrastive Learning of Visual Representatoins" SimCLR☆33Updated 3 years ago