code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
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Updated
Feb 22, 2024 - Python
code released for our ICML 2020 paper "Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation"
code for our TPAMI 2021 paper "Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer"
Source code of our submission (Rank 1) for Multi-Source Domain Adaptation task in VisDA-2019
code for our CVPR 2022 paper "DINE: Domain Adaptation from Single and Multiple Black-box Predictors"
Transfer learning for multi source EEG-emotion-classification
Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark
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
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)
Multi-Source Domain Adaptation via Optimal Transport for Student-Teacher Learning - UAI 2021
Pytorch implementation of DAC-Net ("Zhongying Deng, Kaiyang Zhou, Yongxin Yang, Tao Xiang. Domain Attention Consistency for Multi-Source Domain Adaptation. BMVC 2021")
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" (AAAI 2024)
Wasserstein Aggregation Domain Network
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