ondrejbohdal / label-distillationLinks
Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”
☆42Updated 4 years ago
Alternatives and similar repositories for label-distillation
Users that are interested in label-distillation are comparing it to the libraries listed below
Sorting:
- [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…☆82Updated 3 years ago
- [CVPR 2021] "The Lottery Tickets Hypothesis for Supervised and Self-supervised Pre-training in Computer Vision Models" Tianlong Chen, Jon…☆68Updated 2 years ago
- "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).☆51Updated 4 years ago
- Code for "Transfer Learning without Knowing: Reprogramming Black-box Machine Learning Models with Scarce Data and Limited Resources". (IC…☆38Updated 4 years ago
- [TPAMI 2019] The implementation for "Direction Concentration Learning: Enhancing Congruency in Machine Learning"☆23Updated 5 years ago
- Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)☆113Updated last year
- [NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Z…☆125Updated 3 years ago
- Code for paper "Not All Unlabeled Data are Equal: Learning to Weight Data in Semi-supervised Learning", Ren et al., NeurIPS'20☆25Updated 4 years ago
- Smooth Adversarial Training☆68Updated 4 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- Data-free knowledge distillation using Gaussian noise (NeurIPS paper)☆15Updated 2 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Official PyTorch implementation of "Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity" (ICLR'21 Oral)☆106Updated 3 years ago
- Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"☆142Updated 5 years ago
- [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning☆85Updated 3 years ago
- MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)☆109Updated 2 years ago
- ☆33Updated 4 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆122Updated 3 years ago
- This repository provides code for "On Interaction Between Augmentations and Corruptions in Natural Corruption Robustness".☆45Updated 2 years ago
- A Closer Look at Accuracy vs. Robustness☆88Updated 4 years ago
- Compressing Representations for Self-Supervised Learning☆78Updated 4 years ago
- Unofficial pytorch implementation of Fourier Heat Map proposed in 'A Fourier Perspective on Model Robustness in Computer Vision' [Yin+, N…☆75Updated last year
- On the Importance of Gradients for Detecting Distributional Shifts in the Wild☆56Updated 3 years ago
- Soft-Label Dataset Distillation and Text Dataset Distillation☆74Updated 2 years ago
- baseline mode for the ObjectNet competition☆18Updated 4 years ago
- ☆58Updated 2 years ago
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆22Updated 3 years ago
- Code for CVPR2021 paper: MOOD: Multi-level Out-of-distribution Detection☆38Updated last year
- Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes☆23Updated 5 years ago
- Repo for the paper "Extrapolating from a Single Image to a Thousand Classes using Distillation"☆37Updated last year