gifford-lab / overinterpretationLinks
Code for Overinterpretation paper
☆19Updated 2 years ago
Alternatives and similar repositories for overinterpretation
Users that are interested in overinterpretation are comparing it to the libraries listed below
Sorting:
- PixMix: Dreamlike Pictures Comprehensively Improve Safety Measures (CVPR 2022)☆110Updated 3 years ago
- MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)☆109Updated 3 years ago
- ☆46Updated 5 years ago
- ☆57Updated 4 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆123Updated 4 years ago
- Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training wi…☆54Updated 4 years ago
- ☆111Updated 2 years ago
- ☆36Updated 3 years ago
- Robustness and adaptation of ImageNet scale models. Pre-Release, stay tuned for updates.☆137Updated 2 years ago
- Code for the paper "A Whac-A-Mole Dilemma Shortcuts Come in Multiples Where Mitigating One Amplifies Others"☆50Updated last year
- Code to replicate the key results from Exploring the Limits of Out-of-Distribution Detection (https://arxiv.org/abs/2106.03004) by Stanis…☆44Updated 4 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 5 years ago
- [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…☆125Updated 4 years ago
- baseline mode for the ObjectNet competition☆18Updated 5 years ago
- The official repository for "Intermediate Layers Matter in Momentum Contrastive Self Supervised Learning" paper.☆40Updated 3 years ago
- Learning from Failure: Training Debiased Classifier from Biased Classifier (NeurIPS 2020)☆94Updated 5 years ago
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆56Updated 3 years ago
- ☆34Updated 7 months ago
- ☆47Updated 3 years ago
- ImageNet Testbed, associated with the paper "Measuring Robustness to Natural Distribution Shifts in Image Classification."☆119Updated 2 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆36Updated 3 years ago
- ☆96Updated 3 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated 2 years ago
- Data for "Datamodels: Predicting Predictions with Training Data"☆97Updated 2 years ago
- LISA for ICML 2022☆52Updated 2 years ago
- Code release for paper Extremely Simple Activation Shaping for Out-of-Distribution Detection☆55Updated last year
- ☆29Updated last year
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Official Pytorch implementation of ReBias (Learning De-biased Representations with Biased Representations), ICML 2020☆175Updated last year
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated 2 years ago