code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"

Meta Self-learning for Multi-Source Domain Adaptation： A Benchmark

code for our TPAMI 2021 paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"

code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"

Source code of our submission (Rank 1) for Multi-Source Domain Adaptation task in VisDA-2019

This repo contains the implementation of the Wasserstein Barycenter Transport proposed in "Wasserstein Barycenter Transport for Acoustic Adaptation" at ICASSP21 and "Wasserstein Barycenter for Multi-Source Domain Adaptation" in CVPR21

Pytorch implementation of DAC-Net ("Zhongying Deng, Kaiyang Zhou, Yongxin Yang, Tao Xiang. Domain Attention Consistency for Multi-Source Domain Adaptation. BMVC 2021")

Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning - UAI 2021

Transfer learning for multi source EEG-emotion-classification

Pytorch implementation for "Dynamic Instance Domain Adaptation" (DIDA-Net, accepted to IEEE T-IP).

The official repository for "Information-theoretic regularization for multi-source domain adaptation"

Source codes and datasets for paper "Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives" (AAAI2024)

Wasserstein Aggregation Domain Network

"Multi-Source Collaborative Contrastive Learning for Decentralized Domain Adaptation", IEEE TCSVT

"Exploring Instance Relation for Decentralized Multi-Source Domain Adaptation", ICASSP 2023

Source codes and datasets for paper "Zero-1-to-3: Domain-level Zero-shot Cognitive Diagnosis via One Batch of Early-bird Students towards Three Diagnostic Objectives" (AAAI 2024)