https://github.com/HanjiangHu/DIFL-FCL
공식 코드Retrieval-based Localization Based on Domain-invariant Feature Learning under Changing Environments
Papers with Code 아카이브
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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Hanjun-Dai/sdvae
공식 코드https://github.com/HaroldErbin/nnqft
공식 코드Renormalization in the neural network-quantum field theory correspondence
https://github.com/Harry-Thasarathan/TCVC
공식 코드https://github.com/HazeDT/WaveletKernelNet
공식 코드WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis
https://github.com/HealthX-Lab/DiffusionSynCTSeg
공식 코드https://github.com/Heidelberg-NLP/amr-metric-suite
공식 코드https://github.com/Heidelberg-NLP/xsrl_mbert_aligner
공식 코드X-SRL: A Parallel Cross-Lingual Semantic Role Labeling Dataset
https://github.com/HelenMao/MSGAN
공식 코드Mode Seeking Generative Adversarial Networks for Diverse Image Synthesis
https://github.com/HelenMao/SAVI2I
공식 코드Continuous and Diverse Image-to-Image Translation via Signed Attribute Vectors
https://github.com/Helsinki-NLP/OPUS-MT-train
공식 코드https://github.com/Helsinki-NLP/Tatoeba-Challenge
공식 코드The Tatoeba Translation Challenge -- Realistic Data Sets for Low Resource and Multilingual MT
https://github.com/HeranYang/Hyper-GAN
공식 코드A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation
https://github.com/HideUnderBush/UI2I_via_StyleGAN2
공식 코드Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network
https://github.com/HieuPhan33/MaskGAN
공식 코드Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation
https://github.com/Hindawi91/Pseudo_Supervised_Metrics
공식 코드https://github.com/HsinYingLee/DRIT
공식 코드Diverse Image-to-Image Translation via Disentangled Representations
https://github.com/IBM/Graph2Tree
공식 코드https://github.com/IBM/transition-amr-parser
공식 코드https://github.com/IDSIA/FL-Bioinformatics
공식 코드Technical Insights and Legal Considerations for Advancing Federated Learning in Bioinformatics
https://github.com/IGLICT/DeepFaceDrawing-Jittor
공식 코드https://github.com/IITB-OpenOCRCorrect/iitb-openocr-digit-tool
공식 코드UDAAN: Machine Learning based Post-Editing tool for Document Translation
https://github.com/IS2AI/SpeakingFaces
공식 코드https://github.com/IVRL/ComicsDepth
공식 코드https://github.com/IljaManakov/HDcycleGAN
공식 코드Noise as Domain Shift: Denoising Medical Images by Unpaired Image Translation
https://github.com/Imagist-Shuo/UNMT-SPR
공식 코드Unsupervised Neural Machine Translation with SMT as Posterior Regularization
https://github.com/ImperialNLP/BertGen
공식 코드https://github.com/ImperialNLP/MMT-Delib
공식 코드https://github.com/ImperialNLP/pysimt
공식 코드https://github.com/Intelligent-CAT-Lab/AlphaTrans
공식 코드https://github.com/ItzikMalkiel/AGB
공식 코드Adaptive Gradient Balancing for UndersampledMRI Reconstruction and Image-to-Image Translation
https://github.com/IyatomiLab/LeafGAN
공식 코드LeafGAN: An Effective Data Augmentation Method for Practical Plant Disease Diagnosis
https://github.com/Izecson/fairseq-editor
공식 코드https://github.com/Izecson/saml-nmt
공식 코드Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation
https://github.com/JC230903/NLP-low-resource-pipeline-for-indian-languages/tree/main/pythonversion
공식 코드Low-Resource Language Processing: An OCR-Driven Summarization and Translation Pipeline
https://github.com/JOP-Lee/READ-Large-Scale-Neural-Scene-Rendering-for-Autonomous-Driving
공식 코드READ: Large-Scale Neural Scene Rendering for Autonomous Driving
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.