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daoyuan98 avatar

daoyuan98/MDDA

0
View on GitHub↗
59 stars·13 forks·Python·7 views

MDDA

Implementation of paper multi-source distilling domain adaptation

Features

  • Multi-Source Adaptation - Multi-source distilling domain adaptation.

Star history

Star history chart for daoyuan98/mddaStar history chart for daoyuan98/mdda

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

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Frequently asked questions

What does daoyuan98/mdda do?

Implementation of paper multi-source distilling domain adaptation

What are the main features of daoyuan98/mdda?

The main features of daoyuan98/mdda are: Multi-Source Adaptation.

Which projects share features with daoyuan98/mdda?

Projects with overlapping indexed features include: altschulerwu-lab/mulann — Code and data of the "Multi-domain adversarial learning" paper, Schoenauer-Sebag et al., accepted at ICLR 2019. bupt-ai-cz/meta-selflearning — Meta Self-learning for Multi-Source Domain Adaptation: A Benchmark. chrisallenming/ltc-msda — Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020). eddardd/wbtransport — (ICASSP'21/CVPR'21) Wasserstein Barycenter Transport. francis0625/graphical-modeling-for-multi-source-domain-adaptation — Implementation of Graphical Modeling for Multi-Source Domain Adaptation (TPAMI). hcplab-sysu/msda.

Projects sharing features with MDDA

These projects share indexed features with MDDA. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • bupt-ai-cz/meta-selflearningbupt-ai-cz avatar

    bupt-ai-cz/Meta-SelfLearning

    205View on GitHub↗

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

    Python
    View on GitHub↗205
  • chrisallenming/ltc-msdaChrisAllenMing avatar

    ChrisAllenMing/LtC-MSDA

    75View on GitHub↗

    Implementation of Learning to Combine: Knowledge Aggregation for Multi-Source Domain Adaptation (ECCV 2020).

    Python
    View on GitHub↗75
  • eddardd/wbtransporteddardd avatar

    eddardd/WBTransport

    32View on GitHub↗

    (ICASSP'21/CVPR'21) Wasserstein Barycenter Transport

    Python
    View on GitHub↗32
  • altschulerwu-lab/mulannAltschulerWu-Lab avatar

    AltschulerWu-Lab/MuLANN

    38View on GitHub↗

    Code and data of the "Multi-domain adversarial learning" paper, Schoenauer-Sebag et al., accepted at ICLR 2019

    Lua
    View on GitHub↗38
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