yangze01 / Distilling_the_Knowledge_in_a_Neural_Network_pytorch
☆22Updated 2 years ago
Alternatives and similar repositories for Distilling_the_Knowledge_in_a_Neural_Network_pytorch:
Users that are interested in Distilling_the_Knowledge_in_a_Neural_Network_pytorch are comparing it to the libraries listed below
- PyTorch implementation of "Distilling the Knowledge in a Neural Network" for model compression☆58Updated 7 years ago
- Pytorch implementation of Virtual Adversarial Training☆133Updated 5 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated last year
- Code for paper "Dimensionality-Driven Learning with Noisy Labels" - ICML 2018☆58Updated 9 months ago
- Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)☆71Updated 5 years ago
- PyTorch library for adversarial attack and training☆145Updated 6 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 4 years ago
- A PyTorch implementation for Asymmetric Tri-training for Unsupervised Domain Adaptation☆44Updated 7 years ago
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- Max Mahalanobis Training (ICML 2018 + ICLR 2020)☆90Updated 4 years ago
- Self-Paced Multi-view Co-training for person re-id experiment☆30Updated 3 years ago
- Open category classification by adversarial sample generation☆20Updated 4 years ago
- NeurIPS 2019 : Learning to Propagate for Graph Meta-Learning☆36Updated 5 years ago
- Unofficial pytorch implementation of Born-Again Neural Networks.☆53Updated 4 years ago
- TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER☆118Updated 7 years ago
- Adversarial Defense for Ensemble Models (ICML 2019)☆61Updated 4 years ago
- code for "Training Interpretable Convolutional NeuralNetworks by Differentiating Class-specific Filters"☆27Updated last year
- Official Implementation of MEAL: Multi-Model Ensemble via Adversarial Learning on AAAI 2019☆177Updated 5 years ago
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆81Updated 5 years ago
- Keras implementation of knowledge distillation(Hinton, et al. 2015)☆19Updated 6 years ago
- Further improve robustness of mixup-trained models in inference (ICLR 2020)☆60Updated 4 years ago
- Pytorch implementation of the paper Bayesian Generative Active Deep Learning (ICML 2019).☆24Updated 5 years ago
- ☆9Updated last year
- Meta-Learning based Noise-Tolerant Training☆123Updated 4 years ago
- Q. Yao, H. Yang, B. Han, G. Niu, J. Kwok. Searching to Exploit Memorization Effect in Learning from Noisy Labels. ICML 2020☆22Updated 4 years ago
- Interpreting CNN Knowledge via an Explanatory Graph☆69Updated 4 years ago
- ☆19Updated 6 years ago
- ☆25Updated 5 years ago
- Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network☆62Updated 5 years ago
- a respectively concise Implemention of Maml in Module way☆29Updated 5 years ago