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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

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보존된 평가 기록

5

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/enhuiz/transformer-pytorch

Attention Is All You Need

https://github.com/ensta-u2is/torch-uncertainty

When Does Label Smoothing Help?

https://github.com/enstan/pix2pix_h5-

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/eonr/CompVision

Spatial Transformer Networks

https://github.com/epfml/sent2vec

Robust Cross-lingual Embeddings from Parallel Sentences

https://github.com/epochlab/xres

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/eps696/stargan2

StarGAN v2: Diverse Image Synthesis for Multiple Domains

https://github.com/eric-erki/-lidar_camera_calibration

LiDAR-Camera Calibration using 3D-3D Point correspondences

https://github.com/eric-erki/decaNLP

The Natural Language Decathlon: Multitask Learning as Question Answering

https://github.com/eric-mitchell/mend

Editable Neural Networks

https://github.com/eric-mitchell/serac

Editable Neural Networks

https://github.com/eric-xw/Video-guided-Machine-Translation

VATEX: A Large-Scale, High-Quality Multilingual Dataset for Video-and-Language Research

https://github.com/erickrf/autoencoder

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

https://github.com/ericperfect/Bert_Position_BiLSTM_Attention_CRF_LSTMDecoder

Attention Is All You Need

https://github.com/eriklindernoren/Keras-GAN

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/eriklindernoren/PyTorch-GAN

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/ermongroup/alignflow

AlignFlow: Cycle Consistent Learning from Multiple Domains via Normalizing Flows

https://github.com/escuccim/vaegan-pytorch

Autoencoding beyond pixels using a learned similarity metric

https://github.com/eske/multivec

BilBOWA: Fast Bilingual Distributed Representations without Word Alignments

https://github.com/esteimle/teaser

TEASER: Fast and Certifiable Point Cloud Registration

https://github.com/ethancaballero/neural-engineers-first-attempt

Attention Is All You Need

https://github.com/euiyulsong/EncoderDecoder

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

https://github.com/eunseo1092/Graduation_project

Attention Is All You Need

https://github.com/evanthebouncy/stoicastic_beam

Stochastic Beams and Where to Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement

https://github.com/evtaktasheva/dependency_extraction

Multilingual Denoising Pre-training for Neural Machine Translation

https://github.com/ewrfcas/QANet_keras

QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

https://github.com/exa-labs/exa-mcp-server

Attention Is All You Need

https://github.com/extensive-nlp/TSAI-DeepNLP-END2.0

Attention Is All You Need

https://github.com/facebookresearch/GENRE

BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

https://github.com/facebookresearch/MLQA

Cross-lingual Language Model Pretraining

https://github.com/facebookresearch/MultipleAttributeTextRewriting

Multiple-Attribute Text Style Transfer

https://github.com/facebookresearch/Non-adversarialTranslation

Non-Adversarial Unsupervised Word Translation

https://github.com/facebookresearch/ParlAI

Convolutional Sequence to Sequence Learning

https://github.com/facebookresearch/TransCoder

Unsupervised Translation of Programming Languages

https://github.com/facebookresearch/XLM

Phrase-Based & Neural Unsupervised Machine Translation

https://github.com/facebookresearch/XNLI

XNLI: Evaluating Cross-lingual Sentence Representations

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