https://github.com/LynnHo/AttGAN-Tensorflow
Autoencoding beyond pixels using a learned similarity metric
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/LynnHo/CycleGAN-Tensorflow-2
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/LynnHo/CycleGAN-Tensorflow-PyTorch-Simple
Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks
https://github.com/MCLYang/RhythmGAN_pytorch
https://github.com/MChen9/TCN
An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling
https://github.com/MIT-SPARK/CertifiablyRobustPerception
https://github.com/MIhappen/CaffeSourceCode
R-FCN: Object Detection via Region-based Fully Convolutional Networks
https://github.com/MLX15/TecoGAN
Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation
https://github.com/MOHAMEDELDAKDOUKY/bert_adjusted
https://github.com/MS-Mind/MS-Code-01/tree/main/seq2seq
Lossless Acceleration for Seq2seq Generation with Aggressive Decoding
https://github.com/MS-Mind/MS-Code-06/tree/main/Pix2Pix
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/MS-P3/code7/tree/main/whisper
Reproducing Whisper-Style Training Using an Open-Source Toolkit and Publicly Available Data
https://github.com/MS-P3/code7/tree/main/xlm
https://github.com/MS-P3/code7/tree/main/xlm_roberta
https://github.com/Ma-Dan/Yolact-CoreML
https://github.com/MaLA-LM/emma-500
Massively Multilingual Adaptation of Large Language Models Using Bilingual Translation Data
https://github.com/MaZhiyuanBUAA/bert-tf1.4.0
https://github.com/Maab-Nimir/Neural-Machine-Translation-by-Jointly-Learning-to-Align-and-Translate
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/ManzoorElahi/organic-chemistry-reaction-prediction-using-NMT
https://github.com/Maple728/transformer
https://github.com/MarSaKi/NvEM
https://github.com/MaratSaidov/source-code-summarization
https://github.com/MarcBS/keras
https://github.com/MariaPdg/fmri-reconstruction
Autoencoding beyond pixels using a learned similarity metric
https://github.com/MarvinLavechin/imagetranslation-tensorflow
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/Masao-Taketani/StarGAN-tf2
StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translation
https://github.com/MashaKubyshina/learning_ML
https://github.com/MasoumehVahedi/Pix2Pix-GAN-model
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/MattSegal/speech-enhancement
MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis
https://github.com/Matthewdowney18/Transformer_Dialogue
https://github.com/Matthewdowney18/Yelp_attention
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/Matthewdowney18/Yelp_seq2seq
Neural Machine Translation by Jointly Learning to Align and Translate
https://github.com/Maxencephilbert/In_Silico_Labeling_CBIO_internship
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Flow_Straight_and_Fast_Learning_to_Generate_and_Transfer_Data_with_Rectified_Flow
Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Image_to_Image_Translation_with_Conditional_Adversarial_Nets
Image-to-Image Translation with Conditional Adversarial Networks
https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/On_the_Variance_of_the_Adaptive_Learning_Rate_and_Beyond
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.