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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/alsace08/meta-reasoning

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Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models

https://github.com/alshami52/COOOL_benchmark

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COOOL: Challenge Of Out-Of-Label A Novel Benchmark for Autonomous Driving

https://github.com/altndrr/clup

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Cluster-level pseudo-labelling for source-free cross-domain facial expression recognition

https://github.com/alusi123/dfa

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Dual-stream Feature Augmentation for Domain Generalization

https://github.com/amano-aki/mixture-of-domain-adapters

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Mixture-of-Domain-Adapters: Decoupling and Injecting Domain Knowledge to Pre-trained Language Models Memories

https://github.com/amanpriyanshu/adaptkeybert

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AdaptKeyBERT: An Attention-Based approach towards Few-Shot & Zero-Shot Domain Adaptation of KeyBERT

https://github.com/ambekarsameer96/GLSS

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Unsupervised Domain Adaptation for Semantic Segmentation of NIR Images through Generative Latent Search

https://github.com/ambekarsameer96/generalizeformer

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GeneralizeFormer: Layer-Adaptive Model Generation across Test-Time Distribution Shifts

https://github.com/ameliajimenez/curriculum-federated-learning

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Memory-aware curriculum federated learning for breast cancer classification

https://github.com/amirmael/semisupmde

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Consistency Regularisation for Unsupervised Domain Adaptation in Monocular Depth Estimation

https://github.com/amitaybar/domain-adaptation-for-doa-estimation-in-multipath-channels-with-interferences

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Domain Adaptation for DoA Estimation in Multipath Channels with Interferences

https://github.com/amitrozner/domain-generalizable-multiple-domain-clustering

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Domain-Generalizable Multiple-Domain Clustering

https://github.com/amodas/PRIME-augmentations

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PRIME: A few primitives can boost robustness to common corruptions

https://github.com/amosy3/MUST

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Teacher-Student Consistency For Multi-Source Domain Adaptation

https://github.com/amritabh/conda-gen-text-detection

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ConDA: Contrastive Domain Adaptation for AI-generated Text Detection

https://github.com/amy-hyunji/lora-for-retrieval

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Back to Basics: A Simple Recipe for Improving Out-of-Domain Retrieval in Dense Encoders

https://github.com/amzn/xfer

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Fast Adaptation with Linearized Neural Networks

https://github.com/anan0110692/geoai-foundgen

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A Sensor Agnostic Domain Generalization Framework for Leveraging Geospatial Foundation Models: Enhancing Semantic Segmentation viaSynergistic Pseudo-Labeling and Generative Learning

https://github.com/andongdeng/bear

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A Large-scale Study of Spatiotemporal Representation Learning with a New Benchmark on Action Recognition

https://github.com/andre-sacilotti/transferattn-project-code

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Transferable-guided Attention Is All You Need for Video Domain Adaptation

https://github.com/andreYoo/VeRI_SSML_FD

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Unsupervised Vehicle Re-Identification via Self-supervised Metric Learning using Feature Dictionary

https://github.com/andreeaiana/nase

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News Without Borders: Domain Adaptation of Multilingual Sentence Embeddings for Cross-lingual News Recommendation

https://github.com/andrewcaunes/ia4markings

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seg_3D_by_PC2D: Multi-View Projection for Domain Generalization and Adaptation in 3D Semantic Segmentation

https://github.com/andreyoo/ctam-ctacl-vvreid

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Camera-Tracklet-Aware Contrastive Learning for Unsupervised Vehicle Re-Identification

https://github.com/andy194673/joust

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Transferable Dialogue Systems and User Simulators

https://github.com/anewgithubname/gradest2

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Minimizing $f$-Divergences by Interpolating Velocity Fields

https://github.com/aniketde/DomainGeneralizationMarginal

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Domain Generalization by Marginal Transfer Learning

https://github.com/aniketde/ZeroShotDG

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Zero Shot Domain Generalization

https://github.com/anindyasarkariith/vas

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A Visual Active Search Framework for Geospatial Exploration

https://github.com/anishmadan23/B-SMALL

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B-SMALL: A Bayesian Neural Network approach to Sparse Model-Agnostic Meta-Learning

https://github.com/anita-hu/sim2real-lane-detection

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Sim-to-Real Domain Adaptation for Lane Detection and Classification in Autonomous Driving

https://github.com/anita-hu/simulanes

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Sim-to-Real Domain Adaptation for Lane Detection and Classification in Autonomous Driving

https://github.com/anitarau/domain-gap-reduction-endoscopy

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Task-guided Domain Gap Reduction for Monocular Depth Prediction in Endoscopy

https://github.com/ankanbhunia/AdverseBiNet

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Improving Document Binarization via Adversarial Noise-Texture Augmentation

https://github.com/anneroseeichel/eacl2023_made-of-steel

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Made of Steel? Learning Plausible Materials for Components in the Vehicle Repair Domain

https://github.com/anonymousaccount0/dbal

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Discrepancy-Based Active Learning for Domain Adaptation

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