da2so / Data-Free_Network_Quantization_With_Adversarial_Knowledge_DistillationLinks
Data-Free Network Quantization With Adversarial Knowledge Distillation PyTorch
☆30Updated 4 years ago
Alternatives and similar repositories for Data-Free_Network_Quantization_With_Adversarial_Knowledge_Distillation
Users that are interested in Data-Free_Network_Quantization_With_Adversarial_Knowledge_Distillation are comparing it to the libraries listed below
Sorting:
- Code and checkpoints of compressed networks for the paper titled "HYDRA: Pruning Adversarially Robust Neural Networks" (NeurIPS 2020) (ht…☆91Updated 3 years ago
- [AAAI-2022] Up to 100x Faster Data-free Knowledge Distillation☆76Updated 3 years ago
- [ICLR 2021 Spotlight Oral] "Undistillable: Making A Nasty Teacher That CANNOT teach students", Haoyu Ma, Tianlong Chen, Ting-Kuei Hu, Che…☆82Updated 4 years ago
- [ICLR 2021] "Robust Overfitting may be mitigated by properly learned smoothening" by Tianlong Chen*, Zhenyu Zhang*, Sijia Liu, Shiyu Chan…☆49Updated 4 years ago
- pytorch implementation of Parametric Noise Injection for adversarial defense☆45Updated 6 years ago
- One-Pixel Shortcut: on the Learning Preference of Deep Neural Networks (ICLR 2023 Spotlight)☆14Updated 3 months ago
- Pytorch implementation of Adversarially Robust Distillation (ARD)☆59Updated 6 years ago
- Data-free knowledge distillation using Gaussian noise (NeurIPS paper)☆15Updated 2 years ago
- ZSKD with PyTorch☆31Updated 2 years ago
- A generic code base for neural network pruning, especially for pruning at initialization.☆31Updated 3 years ago
- [NeurIPS'2019] Shupeng Gui, Haotao Wang, Haichuan Yang, Chen Yu, Zhangyang Wang, Ji Liu, “Model Compression with Adversarial Robustness: …☆49Updated 4 years ago
- Implementation of Effective Sparsification of Neural Networks with Global Sparsity Constraint☆31Updated 3 years ago
- Official implementation of "Removing Batch Normalization Boosts Adversarial Training" (ICML'22)☆19Updated 3 years ago
- [NeurIPS‘2021] "MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge", Geng Yuan, Xiaolong Ma, Yanzhi Wang et al…☆18Updated 3 years ago
- Tiny Imagenet Visual Recognition Challenge☆38Updated 7 years ago
- ☆23Updated 5 years ago
- [IJCAI-2021] Contrastive Model Inversion for Data-Free Knowledge Distillation☆73Updated 3 years ago
- Code for the paper "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"☆34Updated 5 years ago
- [NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yon…☆13Updated 3 years ago
- [ICML 2021] "Efficient Lottery Ticket Finding: Less Data is More" by Zhenyu Zhang*, Xuxi Chen*, Tianlong Chen*, Zhangyang Wang☆26Updated 4 years ago
- ☆108Updated 4 years ago
- [NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks☆34Updated last year
- [ICLR 2022] "Sparsity Winning Twice: Better Robust Generalization from More Efficient Training" by Tianlong Chen*, Zhenyu Zhang*, Pengjun…☆40Updated 3 years ago
- pytorch-tiny-imagenet☆188Updated last week
- Source Code for ICML 2019 Paper "Shallow-Deep Networks: Understanding and Mitigating Network Overthinking"☆37Updated 2 years ago
- Knowledge distillation (KD) from a decision-based black-box (DB3) teacher without training data.☆22Updated 3 years ago
- Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"☆144Updated 5 years ago
- Adversarial Defense for Ensemble Models (ICML 2019)☆61Updated 5 years ago
- Reproducing RigL (ICML 2020) as a part of ML Reproducibility Challenge 2020☆29Updated 4 years ago
- ☆89Updated 3 years ago