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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/Deopoler/DCLGAN-Keras

Dual Contrastive Learning for Unsupervised Image-to-Image Translation

https://github.com/DimasDMM/nlp-completer

Modern Methods for Text Generation

https://github.com/DimasDMM/transformers

Modern Methods for Text Generation

https://github.com/DivaniMandi/myCustomDataset_yolact

YOLACT: Real-time Instance Segmentation

https://github.com/Djmcflush/Quantum-Hackathon

Show and Tell: A Neural Image Caption Generator

https://github.com/Doffery/BERT-Sentiment-Analysis-Amazon-Review

Attention Is All You Need

https://github.com/DojunPark/Machine_Translation

Korean-English Machine Translation with Multiple Tokenization Strategy

https://github.com/DorinK/Assignment-2-Neural-Machine-Translation

Effective Approaches to Attention-based Neural Machine Translation

https://github.com/DreamInvoker/LookaheadOptimizer-mx-implementation

Lookahead Optimizer: k steps forward, 1 step back

https://github.com/DwightFoster/Pytorch-TecoGan

Learning Temporal Coherence via Self-Supervision for GAN-based Video Generation

https://github.com/Eamin-sust/tensor2tensor

Tensor2Tensor for Neural Machine Translation

https://github.com/EdinburghNLP/XSum

Convolutional Sequence to Sequence Learning

https://github.com/EdinburghNLP/code-docstring-corpus

Neural Machine Translation of Rare Words with Subword Units

https://github.com/Edresson/VoiceSplit

Stochastic Gradient Methods with Layer-wise Adaptive Moments for Training of Deep Networks

https://github.com/Eeun-ju/NLP-study

A Survey on Deep Learning for Named Entity Recognition

https://github.com/Electro1111/COVID_19_CXR_CLASSIFICATION

XLSor: A Robust and Accurate Lung Segmentor on Chest X-Rays Using Criss-Cross Attention and Customized Radiorealistic Abnormalities Generation

https://github.com/ElenaRyumina/EMO-AffectNetModel

When Does Label Smoothing Help?

https://github.com/EmilioTyl/transformers_from_scratch

Attention Is All You Need

https://github.com/Emir-Liu/Cycle-GAN

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Enigmatisms/Set-Transformer

Attention Is All You Need

https://github.com/Epoch-Mengying/Generating-Poetry-with-Chatbot

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/Erra-Ernesto/master

Tensor2Tensor for Neural Machine Translation

https://github.com/EthanWYB/bert-classification

Attention Is All You Need

https://github.com/EugeneSel/EUMT

Attention Is All You Need

https://github.com/EuphoriaYan/ChatRobot-For-Keras2

Neural Machine Translation by Jointly Learning to Align and Translate

https://github.com/EuphoriaYan/bert_component

Attention Is All You Need

https://github.com/Eurus-Holmes/VAG-NMT

A Visual Attention Grounding Neural Model for Multimodal Machine Translation

https://github.com/Eyyub/tensorflow-cyclegan

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/FHomps/ADViSE

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/FaskyCC/TextClassification

Attention Is All You Need

https://github.com/FazedAI/OpenSeq2Seq

Mixed-Precision Training for NLP and Speech Recognition with OpenSeq2Seq

https://github.com/FenHua/transfer_adv

Improving Adversarial Transferability with Gradient Refining

https://github.com/FengJiaChunFromSYSU/Bert

Attention Is All You Need

https://github.com/Fengchenghao1996/MI2T_EE380L

A Universal Music Translation Network

https://github.com/Feynman1999/MgeEditing

Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks

https://github.com/Feynman27/pytorch-detect-rfcn

R-FCN: Object Detection via Region-based Fully Convolutional Networks

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