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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/dreamgonfly/Transformer-pytorch

Attention Is All You Need

https://github.com/dreamnotover/english_chinese_machine_translation_baseline

Attention Is All You Need

https://github.com/drumpt/Transformer

Attention Is All You Need

https://github.com/dseuss/pytorch-lookahead-optimizer

Lookahead Optimizer: k steps forward, 1 step back

https://github.com/dsunivie/deeperwin

Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks

https://github.com/duyunshu/bert-sentiment-analysis

Attention Is All You Need

https://github.com/duyvuleo/Transformer-DyNet

Incorporating Discrete Translation Lexicons into Neural Machine Translation

https://github.com/dwen3232/op-colorization

Image-to-Image Translation with Conditional Adversarial Networks

https://github.com/dxli94/WLASL

TSPNet: Hierarchical Feature Learning via Temporal Semantic Pyramid for Sign Language Translation

https://github.com/dyq0811/EEG-Transformer-seq2seq

Attention Is All You Need

https://github.com/dzqjorking/transpose

Attention Is All You Need

https://github.com/e3nn/e3nn

Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

https://github.com/e3nn/e3nn-jax

Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds

https://github.com/ecmeldmt/AttentionGAN-v0

Attention-Guided Generative Adversarial Networks for Unsupervised Image-to-Image Translation

https://github.com/edchengg/transfusion

Frustratingly Easy Label Projection for Cross-lingual Transfer

https://github.com/eddy4112/Yolact

YOLACT: Real-time Instance Segmentation

https://github.com/edkamb/chisel-tool

Modeling and Verifying Cyber-Physical Systems with Hybrid Active Objects

https://github.com/edward-sun/nat-em

An EM Approach to Non-autoregressive Conditional Sequence Generation

https://github.com/edwardguil/MMTL

A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation

https://github.com/edwardjhu/improved_wasserstein

Wasserstein Adversarial Examples via Projected Sinkhorn Iterations

https://github.com/eff-kay/temp-texar-repo

Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation

https://github.com/effectiff-tech/homogeneity-scripts

ATR4S: Toolkit with State-of-the-art Automatic Terms Recognition Methods in Scala

https://github.com/egshkim/ConditionalBBDM-for-VHR-SAR-to-Optical

BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models

https://github.com/eladrich/pix2vertex.pytorch

Unrestricted Facial Geometry Reconstruction Using Image-to-Image Translation

https://github.com/eleanorye00/Gamifier

Attention Is All You Need

https://github.com/elisejiuqizhang/jax-lmu

Parallelizing Legendre Memory Unit Training

https://github.com/elisiojsj/Kuzushiji-49

Spatial Transformer Networks

https://github.com/elliottd/GroundedTranslation

Multilingual Image Description with Neural Sequence Models

https://github.com/elliottwu/stext2image

Image Generation from Sketch Constraint Using Contextual GAN

https://github.com/elsa9421/cyclegan_readable

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

https://github.com/elvisyjlin/RelGAN-PyTorch

RelGAN: Multi-Domain Image-to-Image Translation via Relative Attributes

https://github.com/emanuele-progr/PSSP

Attention Is All You Need

https://github.com/emjotde/amunmt

Marian: Fast Neural Machine Translation in C++

https://github.com/emrekuecuek/COMP541

Memory-Efficient Adaptive Optimization

https://github.com/enealor/pytorch-sm3

Memory-Efficient Adaptive Optimization

https://github.com/enhuiz/torchnmt

Attention Is All You Need

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