Demo for unsupervised domain adversarial neural network (DANN) using two moons synthetic dataset. Implemented in PyTorch, compared to ADAPT (TensorFlow) for correctness.
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Updated
Aug 19, 2025 - Python
Demo for unsupervised domain adversarial neural network (DANN) using two moons synthetic dataset. Implemented in PyTorch, compared to ADAPT (TensorFlow) for correctness.
🔄 [Signal] Domain adaptation for fault classification using DANN (Source → Target)
Object detection for Domain adaptation with The Pascal VOC 2012 dataset (DANN)
Supervised-Domain-Adaptation
Deep Neural Network Library for JavaScript.
Souce code of "Inter-seasons and Inter-households Domain Adaptation Based on DANNs and Pseudo Labeling for Non-Intrusive Occupancy Detection" (JSAI Journal) + "Two stages domain invariant representation learners solve the large co-variate shift in unsupervised domain adaptation with two dimensional data domains"(https://arxiv.org/abs/2412.04682).
This is the repository of Deep Learning for Computer Vision at National Taiwan University.
Awesome Domain Adaptation Python Toolbox
Domain Adaptation / Transfer Learning in popular datasets (MNIST, SVHN, USPS)
Unsupervised neural domain adaptation for document image binarization
Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
[ICML 2022]Source code for "A Closer Look at Smoothness in Domain Adversarial Training",
Domain Adaptation With Domain-Adversarial Training of Neural Networks
Utilize synthetic data and unlabeled real data to train an image classifier, employing Domain Adaptation techniques.
PyTorch implementation of DANN (Domain-Adversarial Training of Neural Networks)
DANN PyTorch implementation with 2D toy example
[TKDD 2023] AdaTime: A Benchmarking Suite for Domain Adaptation on Time Series Data
Unsupervised Domain Adaptation for Computer Vision Tasks
python 3 pytorch implementation of DANN
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