zju-vipa / Fast-DatafreeLinks
[AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation
☆70Updated 2 years ago
Alternatives and similar repositories for Fast-Datafree
Users that are interested in Fast-Datafree are comparing it to the libraries listed below
Sorting:
- [IJCAI-2021] Contrastive Model Inversion for Data-Free Knowledge Distillation☆72Updated 3 years ago
- ☆86Updated 2 years ago
- Official PyTorch implementation of "Dataset Condensation via Efficient Synthetic-Data Parameterization" (ICML'22)☆113Updated last year
- Data-Free Network Quantization With Adversarial Knowledge Distillation PyTorch☆29Updated 3 years ago
- [NeurIPS-2021] Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data☆44Updated 2 years ago
- Efficient Dataset Distillation by Representative Matching☆113Updated last year
- Code and pretrained models for paper: Data-Free Adversarial Distillation☆99Updated 2 years ago
- Data-Free Knowledge Distillation☆21Updated 3 years ago
- ☆30Updated 3 years ago
- The code of the paper "Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation" (CVPR2023)☆40Updated 2 years ago
- Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…☆92Updated 2 years ago
- ICLR 2024, Towards Lossless Dataset Distillation via Difficulty-Aligned Trajectory Matching☆101Updated last year
- ☆14Updated 2 years ago
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆31Updated 3 years ago
- ☆19Updated 2 years ago
- (Pytorch) Training ResNets on ImageNet-100 data☆60Updated 3 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆47Updated 3 years ago
- This repository is the official implementation of Dataset Condensation with Contrastive Signals (DCC), accepted at ICML 2022.☆21Updated 2 years ago
- [ICLR'23] Trainability Preserving Neural Pruning (PyTorch)☆32Updated 2 years ago
- Code of Data-Free Knowledge Distillation via Feature Exchange and Activation Region Constraint☆17Updated last year
- PyTorch implementation of paper "Dataset Distillation via Factorization" in NeurIPS 2022.☆66Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆30Updated 2 years ago
- ☆28Updated last year
- [TPAMI 2023] Low Dimensional Landscape Hypothesis is True: DNNs can be Trained in Tiny Subspaces☆40Updated 2 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 (KD) from a decision-based black-box (DB3) teacher without training data.☆21Updated 3 years ago
- Official implementation of "Removing Batch Normalization Boosts Adversarial Training" (ICML'22)☆19Updated 2 years ago
- An Numpy and PyTorch Implementation of CKA-similarity with CUDA support☆91Updated 4 years ago
- Official implementation of "When Adversarial Training Meets Vision Transformers: Recipes from Training to Architecture" published at Neur…☆33Updated 8 months ago
- Query-Efficient Data-Free Learning from Black-Box Models☆22Updated 2 years ago