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Unsupervised Domain Adaptation

Notebooks

These notebooks contain runnable paper implementations:

Papers

AdaBN

Revisiting Batch Normalization For Practical Domain Adaptation

Docs coming soon

ADDA

Adversarial Discriminative Domain Adaptation

AFN

Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation

ATDOC

Domain Adaptation with Auxiliary Target Domain-Oriented Classifier

BNM

Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

BSP

Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation

CDAN

Conditional Adversarial Domain Adaptation

CORAL

Deep CORAL: Correlation Alignment for Deep Domain Adaptation

DANN

Domain-Adversarial Training of Neural Networks

Domain Confusion

Simultaneous Deep Transfer Across Domains and Tasks

GAN

GVB

Gradually Vanishing Bridge for Adversarial Domain Adaptation

IM

ITL

Information-Theoretical Learning of Discriminative Clusters for Unsupervised Domain Adaptation

Docs coming soon

JMMD

Deep Transfer Learning with Joint Adaptation Networks

MCC

Minimum Class Confusion for Versatile Domain Adaptation

MCD

Maximum Classifier Discrepancy for Unsupervised Domain Adaptation

MMD

Learning Transferable Features with Deep Adaptation Networks

RTN

Unsupervised Domain Adaptation with Residual Transfer Networks

STAR

Stochastic Classifiers for Unsupervised Domain Adaptation

SWD

Sliced Wasserstein Discrepancy for Unsupervised Domain Adaptation

SymNets

Domain-Symmetric Networks for Adversarial Domain Adaptation

VADA

A DIRT-T Approach to Unsupervised Domain Adaptation