yangze01 / Distilling_the_Knowledge_in_a_Neural_Network_pytorchLinks
☆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
Sorting:
- Pytorch implementation of Virtual Adversarial Training☆134Updated 6 years ago
- TRAINING DEEP NEURAL-NETWORKS USING A NOISE ADAPTATION LAYER☆118Updated 8 years ago
- Self-Paced Multi-view Co-training for person re-id experiment☆30Updated 4 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- A PyTorch implementation for Asymmetric Tri-training for Unsupervised Domain Adaptation☆44Updated 7 years ago
- PyTorch implementation of "Distilling the Knowledge in a Neural Network" for model compression☆58Updated 7 years ago
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆81Updated 6 years ago
- Teaches a student network from the knowledge obtained via training of a larger teacher network☆158Updated 7 years ago
- this project is the code of domain adaptation referenced by unsupervised domain adaptation by backpropagation(http://machinelearning.wust…☆63Updated 7 years ago
- TensorFlow Implementation of Deep Mutual Learning☆322Updated 7 years ago
- This is a collection of Papers and Codes for Noisy Labels Problem.☆63Updated 7 years ago
- Repository for the Learning without Forgetting paper, ECCV 2016☆84Updated 5 years ago
- Open category classification by adversarial sample generation☆20Updated 5 years ago
- extract features by maximizing mutual information☆148Updated 5 years ago
- Unofficial Implement of Asymmetric Tri-training for Unsupervised Domain Adaptation☆40Updated 8 years ago
- Learning What and Where to Transfer (ICML 2019)☆248Updated 4 years ago
- Code for the paper "Joint Domain Alignment and Discriminative Feature Learning for Unsupervised Deep Domain Adaptation" (AAAI-2019)☆42Updated 6 years ago
- Implementations of knowledge distillation and knowledge transfer models in neural networks.☆22Updated 6 years ago
- Code for ICCV2019 "Symmetric Cross Entropy for Robust Learning with Noisy Labels"☆171Updated 4 years ago
- ☆19Updated 7 years ago
- Code release for "Learning Multiple Tasks with Multilinear Relationship Networks" (NIPS 2017)☆71Updated 7 years ago
- Keras implementation of knowledge distillation(Hinton, et al. 2015)☆19Updated 6 years ago
- DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks https://arxiv.org/abs/1901.09229☆66Updated 4 years ago
- Code for paper "Dimensionality-Driven Learning with Noisy Labels" - ICML 2018☆58Updated last year
- ICML 2019: Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels☆91Updated 4 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- Knowledge Distillation with Adversarial Samples Supporting Decision Boundary (AAAI 2019)☆71Updated 5 years ago
- Virtual Adversarial Training (VAT) implementation for PyTorch