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Domain Adaptation

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Domain Adaptation is the task of adapting models across domains. This is motivated by the challenge where the test and training datasets fall from different data distributions due to some factor. Domain adaptation aims to build machine learning models that can be generalized into a target domain and dealing with the discrepancy across domain distributions.

Further readings:

A Brief Review of Domain Adaptation

<span style="color:grey; opacity: 0.6">( Image credit: Unsupervised Image-to-Image Translation Networks )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/yuanjianhao508/notjustprettypictures

공식 코드

Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators

https://github.com/yuanyige/tea

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TEA: Test-time Energy Adaptation

https://github.com/yuanzh/aspect_adversarial

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Aspect-augmented Adversarial Networks for Domain Adaptation

https://github.com/yue-zhongqi/icon

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Make the U in UDA Matter: Invariant Consistency Learning for Unsupervised Domain Adaptation

https://github.com/yue-zhongqi/tcm

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Transporting Causal Mechanisms for Unsupervised Domain Adaptation

https://github.com/yueatsprograms/uda_release

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Unsupervised Domain Adaptation through Self-Supervision

https://github.com/yueeeeeeee/canmd

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Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19

https://github.com/yueeeeeeee/caqa

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Contrastive Domain Adaptation for Question Answering using Limited Text Corpora

https://github.com/yueeeeeeee/self-supervised-qa

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Domain Adaptation for Question Answering via Question Classification

https://github.com/yuhangzang/upt

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Unified Vision and Language Prompt Learning

https://github.com/yuhed/proxymix

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ProxyMix: Proxy-based Mixup Training with Label Refinery for Source-Free Domain Adaptation

https://github.com/yuhuayc/da-faster-rcnn

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Domain Adaptive Faster R-CNN for Object Detection in the Wild

https://github.com/yukilulu/cac

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Contrast and Clustering: Learning Neighborhood Pair Representation for Source-free Domain Adaptation

https://github.com/yukinowan/adapt-retrive-revise

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Reformulating Domain Adaptation of Large Language Models as Adapt-Retrieve-Revise: A Case Study on Chinese Legal Domain

https://github.com/yulearningg/LRDG

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Domain Generalization by Learning and Removing Domain-specific Features

https://github.com/yunfeixie233/vigal

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Play to Generalize: Learning to Reason Through Game Play

https://github.com/yunqing-me/AdAM

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Few-shot Image Generation via Adaptation-Aware Kernel Modulation

https://github.com/yunqing-me/Born-Again-FS

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FS-BAN: Born-Again Networks for Domain Generalization Few-Shot Classification

https://github.com/yuntaodu/CDEM

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Cross-domain error minimization for unsupervised domain adaptation

https://github.com/yuqiu-rgb/uniptms

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UniPTMs: The First Unified Multi-type PTM Site Prediction Model via Master-Slave Architecture-Based Multi-Stage Fusion Strategy and Hierarchical Contrastive Loss

https://github.com/yurongyou/rote-da

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Unsupervised Adaptation from Repeated Traversals for Autonomous Driving

https://github.com/yushu-li/hiltta

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Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection

https://github.com/yushuntang/dct

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Domain-Conditioned Transformer for Fully Test-time Adaptation

https://github.com/yushuntang/dpal

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Dual-Path Adversarial Lifting for Domain Shift Correction in Online Test-time Adaptation

https://github.com/yussef93/selectnadapticcvw

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SelectNAdapt: Support Set Selection for Few-Shot Domain Adaptation

https://github.com/yutianren/multi-cause-slb

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Self-Labeling in Multivariate Causality and Quantification for Adaptive Machine Learning

https://github.com/yuweisunn/federated-knowledge-alignment

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Feature Distribution Matching for Federated Domain Generalization

https://github.com/yuwlong666/fsdg

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Fine-Grained Domain Generalization with Feature Structuralization

https://github.com/yuxin-dong/idm

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How Does Distribution Matching Help Domain Generalization: An Information-theoretic Analysis

https://github.com/yuyongcan/benchmark-tta

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Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification

https://github.com/yuyongcan/stamp

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STAMP: Outlier-Aware Test-Time Adaptation with Stable Memory Replay

https://github.com/yuzhenmao/transnet

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Augmenting Knowledge Transfer across Graphs

https://github.com/yvanyin/filldepth

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Towards Domain-agnostic Depth Completion

https://github.com/yvonneywu/udama

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UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction

https://github.com/ywher/TUFL

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Threshold-adaptive Unsupervised Focal Loss for Domain Adaptation of Semantic Segmentation

https://github.com/ywher/sam4udass

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SAM4UDASS: When SAM Meets Unsupervised Domain Adaptive Semantic Segmentation in Intelligent Vehicles

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