polo5 / ZeroShotKnowledgeTransferLinks
Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"
☆141Updated 5 years ago
Alternatives and similar repositories for ZeroShotKnowledgeTransfer
Users that are interested in ZeroShotKnowledgeTransfer are comparing it to the libraries listed below
Sorting:
- ICCV 2019 Overcoming Catastrophic Forgetting with Unlabeled Data in the Wild☆80Updated 2 years ago
- Zero-Shot Knowledge Distillation in Deep Networks☆67Updated 3 years ago
- ☆108Updated 3 years ago
- Self-supervised Label Augmentation via Input Transformations (ICML 2020)☆105Updated 4 years ago
- [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…☆81Updated 3 years ago
- Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)☆71Updated 5 years ago
- "Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness" (NeurIPS 2020).☆51Updated 4 years ago
- Pre-Training Buys Better Robustness and Uncertainty Estimates (ICML 2019)☆100Updated 3 years ago
- Official implementation of "iTAML : An Incremental Task-Agnostic Meta-learning Approach". CVPR 2020☆97Updated last year
- [TPAMI2022 & NeurIPS2020] Official implementation of Self-Adaptive Training☆128Updated 3 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago
- Official Implementation of "Random Path Selection for Incremental Learning" paper. NeurIPS 2019☆53Updated 2 years ago
- Code and pretrained models for paper: Data-Free Adversarial Distillation☆99Updated 2 years ago
- [CVPR2019]Learning Not to Learn : An adversarial method to train deep neural networks with biased data☆111Updated 5 years ago
- Code for our paper "Informative Dropout for Robust Representation Learning: A Shape-bias Perspective" (ICML 2020)☆125Updated 2 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 5 years ago
- Project page for our paper: Interpreting Adversarially Trained Convolutional Neural Networks☆66Updated 5 years ago
- [CVPR 2020] Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning☆85Updated 3 years ago
- Trained model weights, training and evaluation code from the paper "A simple way to make neural networks robust against diverse image cor…☆61Updated 2 years ago
- Code for the paper "M2m: Imbalanced Classification via Major-to-minor Translation" (CVPR 2020)☆96Updated 3 years ago
- SpotTune: Transfer Learning through Adaptive Fine-tuning☆90Updated 5 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, in ICCV 2019☆58Updated 5 years ago
- PyTorch implementation of Weighted Batch-Normalization layers☆37Updated 5 years ago
- Official PyTorch implementation of “Flexible Dataset Distillation: Learn Labels Instead of Images”☆42Updated 4 years ago
- Unsupervised Domain Adaptation through Self-Supervision☆79Updated 3 years ago
- ☆175Updated 11 months ago
- (NeurIPS 2020) Meta-Consolidation for Continual Learning☆37Updated 4 years ago
- ☆141Updated 4 years ago