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Title: transferlearning/code at master · Engibacter/transferlearning · GitHub

Open Graph Title: transferlearning/code at master · Engibacter/transferlearning

X Title: transferlearning/code at master · Engibacter/transferlearning

Description: Everything about Transfer Learning and Domain Adaptation--迁移学习 - transferlearning/code at master · Engibacter/transferlearning

Open Graph Description: Everything about Transfer Learning and Domain Adaptation--迁移学习 - Engibacter/transferlearning

X Description: Everything about Transfer Learning and Domain Adaptation--迁移学习 - Engibacter/transferlearning

Opengraph URL: https://github.com/Engibacter/transferlearning/tree/master/code

X: @github

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https://github.com/Engibacter/transferlearning
transferlearninghttps://github.com/Engibacter/transferlearning/tree/master
Historyhttps://github.com/Engibacter/transferlearning/commits/master/code
https://github.com/Engibacter/transferlearning/commits/master/code
transferlearninghttps://github.com/Engibacter/transferlearning/tree/master
..https://github.com/Engibacter/transferlearning/tree/master
BDAhttps://github.com/Engibacter/transferlearning/tree/master/code/BDA
BDAhttps://github.com/Engibacter/transferlearning/tree/master/code/BDA
deephttps://github.com/Engibacter/transferlearning/tree/master/code/deep
deephttps://github.com/Engibacter/transferlearning/tree/master/code/deep
distancehttps://github.com/Engibacter/transferlearning/tree/master/code/distance
distancehttps://github.com/Engibacter/transferlearning/tree/master/code/distance
traditionalhttps://github.com/Engibacter/transferlearning/tree/master/code/traditional
traditionalhttps://github.com/Engibacter/transferlearning/tree/master/code/traditional
README.mdhttps://github.com/Engibacter/transferlearning/blob/master/code/README.md
README.mdhttps://github.com/Engibacter/transferlearning/blob/master/code/README.md
README.mdhttps://github.com/Engibacter/transferlearning/tree/master/code#readme
https://github.com/Engibacter/transferlearning/tree/master/code#code_transfer_learning
https://github.com/Engibacter/transferlearning/tree/master/code#fine-tune-最简单的深度迁移学习
PyTorchhttps://github.com/jindongwang/transferlearning/tree/master/code/deep/finetune_AlexNet_ResNet
基于深度学习和迁移学习的识花实践(Tensorflow)https://cosx.org/2017/10/transfer-learning/
基于Pytorch的图像分类https://github.com/miguelgfierro/sciblog_support/blob/master/A_Gentle_Introduction_to_Transfer_Learning/Intro_Transfer_Learning.ipynb
使用Pytorch进行finetunehttps://github.com/Spandan-Madan/Pytorch_fine_tuning_Tutorial
Tensorflowhttps://github.com/tensorflow/hub
Pytorchhttps://github.com/creafz/pytorch-cnn-finetune
https://github.com/Engibacter/transferlearning/tree/master/code#basic-distance-常用的距离度量
Matlabhttps://github.com/lopezpaz/classifier_tests/tree/master/code/unit_test_mmd
Pythonhttps://github.com/jindongwang/transferlearning/tree/master/code/distance/mmd.py
Pythonhttps://github.com/jindongwang/transferlearning/tree/master/code/distance/proxy_a_distance.py
Pythonhttps://github.com/jindongwang/transferlearning/tree/master/code/distance/coral_loss.py
https://github.com/Engibacter/transferlearning/tree/master/code#traditional-transfer-learning-methods--非深度迁移
Matlabhttps://github.com/jindongwang/transferlearning/tree/master/code/traditional/SVM.m
Matlab(Recommended!)https://github.com/jindongwang/transferlearning/blob/master/code/traditional/MyTCA.m
Pythonhttps://github.com/jindongwang/transferlearning/tree/master/code/traditional/TCA_python
Matlabhttps://github.com/jindongwang/transferlearning/blob/master/code/traditional/MyGFK.m
Matlabhttps://github.com/enoonIT/nbnn-nbnl/tree/master/DANBNN_demo
Matlabhttps://github.com/jindongwang/transferlearning/blob/master/code/traditional/MyJDA.m
Matlabhttps://github.com/jindongwang/transferlearning/blob/master/code/traditional/MyTJM.m
Matlabhttps://github.com/jindongwang/transferlearning/blob/master/code/traditional/CORAL
Githubhttps://github.com/VisionLearningGroup/CORAL
Matlab(official)https://www.uow.edu.au/~jz960/codes/JGSA-r.rar
Matlab(easy)https://github.com/jindongwang/transferlearning/blob/master/code/traditional/CORA/MyJGSA.m
Matlabhttps://github.com/jindongwang/transferlearning/tree/master/code/traditional/MyARTL
Pythonhttps://github.com/chenchiwei/tradaboost
Matlab(official)http://users.cecs.anu.edu.au/~basura/DA_SA/
Matlabhttps://github.com/jindongwang/transferlearning/tree/master/code/traditional/SA_SVM.m
Matlab(official)https://github.com/jindongwang/transferlearning/tree/master/code/BDA
Matlabhttps://github.com/xyh2016/MTLF
Matlab(official)https://github.com/Heliot7/open-set-da
Matlab(official)https://github.com/poppinace/TAISL
Matlabhttps://github.com/jindongwang/activityrecognition/tree/master/code/percom18_stl
Matlabhttp://homes.esat.kuleuven.be/~raljundi/papers/LSA%20Clean%20Code.zip
Matlab(official)http://stevenhoi.org/otl
Matlabhttps://github.com/twanvl/rwa-da/tree/master/src
Matlab(Official)https://github.com/jindongwang/transferlearning/tree/master/code/traditional/MEDA
https://github.com/Engibacter/transferlearning/tree/master/code#deep-transfer-learning-methods--深度迁移
PyTorchhttps://github.com/jindongwang/transferlearning/tree/master/code/deep/DaNN
PyTorch(recommend)https://github.com/jindongwang/transferlearning/tree/master/code/deep/DeepCoral
PyTorchhttps://github.com/SSARCandy/DeepCORAL
中文解读https://ssarcandy.tw/2017/10/31/deep-coral/
PyTorch(Official)https://github.com/thuml/Xlearn/tree/master/pytorch
Caffe(Official)https://github.com/thuml/Xlearn
PyTorch(DAN)(recommend)https://github.com/jindongwang/transferlearning/tree/master/code/deep/DAN
Caffehttps://github.com/thuml/Xlearn
Tensorflow(Official)https://github.com/erictzeng/adda
Pytorchhttps://github.com/corenel/pytorch-adda
Pytorch(another)https://github.com/jvanvugt/pytorch-domain-adaptation/blob/master/adda.py
Caffe(Official)https://github.com/ddtm/caffe/tree/grl
Tensorflow(third party)https://github.com/shucunt/domain_adaptation
PyTorchhttps://github.com/fungtion/DANN
Pytorch(another)https://github.com/jvanvugt/pytorch-domain-adaptation/blob/master/revgrad.py
Python(official)https://github.com/GRAAL-Research/domain_adversarial_neural_network
Tensorflowhttps://github.com/jindongwang/tf-dann
Tensorflowhttps://github.com/haeusser/learning_by_association
Matlabhttps://github.com/hemanthdv/da-hash
Python(Keras)https://github.com/samotiian/CCSA
Pytorchhttps://github.com/thuml/MTlearn
Caffehttps://github.com/ducksoup/autodial
Tensorflowhttps://github.com/tensorflow/models/tree/master/research/domain_adaptation
Kerashttps://github.com/ghif/drcn
Pytorchhttps://github.com/fungtion/DRCN
Kerashttps://github.com/ghif/mtae
Matlabhttps://github.com/rahafaljundi/Encoder-Based-Lifelong-learning
Pythonhttps://github.com/pmorerio/minimal-entropy-correlation-alignment
Python(Tensorflow)https://github.com/tolstikhin/wae
Pytorchhttps://github.com/corenel/pytorch-atda#pytorch-atda
Pytorchhttps://github.com/vaibhavnaagar/pixelDA_GAN
Pytorchhttps://github.com/corenel/pytorch-arda
Pytorchhttps://github.com/carpedm20/DiscoGAN-pytorch
Caffe(official)https://github.com/thuml/mada
Pytorch(official)https://github.com/mil-tokyo/MCD_DA
Tensorflowhttps://github.com/ricvolpi/adversarial-feature-augmentation
Tensorflowhttps://github.com/YingZhangDUT/Deep-Mutual-Learning
Pytorchhttps://github.com/Britefury/self-ensemble-visual-domain-adapt
Pytorch(Official)https://github.com/thuml/PADA
Pytorchhttps://github.com/mahfuj9346449/iCAN
Caffehttps://github.com/hellojing89/weightedGANpartialDA
Tensorflowhttps://github.com/Mid-Push/Open_set_domain_adaptation
Pytorchhttps://github.com/jvanvugt/pytorch-domain-adaptation/blob/master/wdgrl.py
Tensorflowhttps://github.com/A-bone1/JDDA
Code from HKUSThttp://www.cse.ust.hk/TL/
https://github.com/Engibacter/transferlearning/tree/master/code#code-from-hkust-a-bit-old
herehttps://github.com/jindongwang/transferlearning/blob/master/doc/dataset.md
https://github.com/Engibacter/transferlearning/tree/master/code#references
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