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Domain Adaptation

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하위 태스크: 13
평가표: 58
보존된 평가 기록: 391

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/thefatbandit/FDA

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Reproducibility of "FDA: Fourier Domain Adaptation forSemantic Segmentation

https://github.com/thefonseca/factorsum

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Factorizing Content and Budget Decisions in Abstractive Summarization of Long Documents

https://github.com/theo2021/onda

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Online Domain Adaptation for Semantic Segmentation in Ever-Changing Conditions

https://github.com/thevoidname/generalized-one-shot-gan-adaption

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Generalized One-shot Domain Adaptation of Generative Adversarial Networks

https://github.com/thibsej/unbalanced_gromov_wasserstein

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The Unbalanced Gromov Wasserstein Distance: Conic Formulation and Relaxation

https://github.com/thongnt99/acl22-depression-phq9

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Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires

https://github.com/thu-coai/KdConv

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KdConv: A Chinese Multi-domain Dialogue Dataset Towards Multi-turn Knowledge-driven Conversation

https://github.com/thu-da-6d-pose-group/self6dpp

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Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimation

https://github.com/thuan2412/a-principled-approach-for-model-validation-for-domain-generalization

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A principled approach to model validation in domain generalization

https://github.com/thuan2412/conditional

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Conditional entropy minimization principle for learning domain invariant representation features

https://github.com/thuan2412/conditional_entropy_minimization_for_domain_generalization

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Conditional entropy minimization principle for learning domain invariant representation features

https://github.com/thuan2412/joint-covariate-alignment-and-concept-alignment-for-domain-generalization

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Joint covariate-alignment and concept-alignment: a framework for domain generalization

https://github.com/thuan2412/tradeoff_between_domain_alignment_and_reconstruction_loss

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Trade-off between reconstruction loss and feature alignment for domain generalization

https://github.com/thudm/moelora_riemannian

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A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models

https://github.com/thudzj/CAT

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Cluster Alignment with a Teacher for Unsupervised Domain Adaptation

https://github.com/thuml/CDAN

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Conditional Adversarial Domain Adaptation

https://github.com/thuml/Decoupled-Adaptation-for-Cross-Domain-Object-Detection

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Decoupled Adaptation for Cross-Domain Object Detection

https://github.com/thuml/MDD

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Bridging Theory and Algorithm for Domain Adaptation

https://github.com/thuml/PADA

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Partial Adversarial Domain Adaptation

https://github.com/thuml/Regressive-Domain-Adaptation-for-Unsupervised-Keypoint-Detection

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Regressive Domain Adaptation for Unsupervised Keypoint Detection

https://github.com/thuml/Transfer-Learning-Library

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Transferability in Deep Learning: A Survey

https://github.com/thuml/Versatile-Domain-Adaptation

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Minimum Class Confusion for Versatile Domain Adaptation

https://github.com/thuml/transfer-caffe

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Unsupervised Domain Adaptation with Residual Transfer Networks

https://github.com/thuml/videodg

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VideoDG: Generalizing Temporal Relations in Videos to Novel Domains

https://github.com/thunlp/Knowledge-Inheritance

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Knowledge Inheritance for Pre-trained Language Models

https://github.com/thunlp/OpenMatch

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CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search

https://github.com/thunlp/deepperception

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DeepPerception: Advancing R1-like Cognitive Visual Perception in MLLMs for Knowledge-Intensive Visual Grounding

https://github.com/thunlp/fewrel

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FewRel 2.0: Towards More Challenging Few-Shot Relation Classification

https://github.com/thunlp/pelt

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A Simple but Effective Pluggable Entity Lookup Table for Pre-trained Language Models

https://github.com/tiankongzhang/mga

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Robust Domain Adaptive Object Detection with Unified Multi-Granularity Alignment

https://github.com/tiankongzhang/mgada

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Multi-Granularity Alignment Domain Adaptation for Object Detection

https://github.com/tiankongzhang/nsa

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Unsupervised Domain Adaptive Detection with Network Stability Analysis

https://github.com/tidbcloud/tiinsight

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Towards Automated Cross-domain Exploratory Data Analysis through Large Language Models

https://github.com/tiffamy/3dod-lsf

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Improving Generalization Ability for 3D Object Detection by Learning Sparsity-invariant Features

https://github.com/tigrangalstyan/wilds

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Failure Modes of Domain Generalization Algorithms

https://github.com/tim-learn/BA3US

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A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.