bethgelab / InDomainGeneralizationBenchmark
☆34Updated 3 years ago
Alternatives and similar repositories for InDomainGeneralizationBenchmark:
Users that are interested in InDomainGeneralizationBenchmark are comparing it to the libraries listed below
- ☆34Updated 3 years ago
- ☆55Updated 4 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆39Updated 4 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆39Updated last year
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- A way to achieve uniform confidence far away from the training data.☆37Updated 3 years ago
- ☆38Updated 3 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- [ICLR'22] Self-supervised learning optimally robust representations for domain shift.☆23Updated 2 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated last year
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆41Updated last year
- Crowdsourcing metrics and test datasets beyond ImageNet (ICML 2022 workshop)☆37Updated 8 months ago
- An Investigation of Why Overparameterization Exacerbates Spurious Correlations☆30Updated 4 years ago
- [NeurIPS'20] Code for the Paper Compositional Visual Generation and Inference with Energy Based Models☆44Updated last year
- Do input gradients highlight discriminative features? [NeurIPS 2021] (https://arxiv.org/abs/2102.12781)☆13Updated 2 years ago
- Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).☆22Updated 2 years ago
- ☆53Updated 6 months ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction☆35Updated 2 years ago
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- Towards Understanding Sharpness-Aware Minimization [ICML 2022]☆35Updated 2 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 2 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 3 years ago
- ☆44Updated 2 years ago
- ☆64Updated 4 years ago
- Code for the paper "Understanding Generalization through Visualizations"☆60Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆68Updated 4 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- ☆49Updated 3 years ago
- Fine-grained ImageNet annotations☆29Updated 4 years ago