Papers with Code 아카이브
Unsupervised Pre-training
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Pre-training a neural network using unsupervised (self-supervised) auxiliary tasks on unlabeled data.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zzk273/freepoint
공식 코드https://github.com/AntonioAcunzo/mvts_transformer
A Transformer-based Framework for Multivariate Time Series Representation Learning
https://github.com/AvocadoAlpha/boltz_bo
How far can we go without convolution: Improving fully-connected networks
https://github.com/CyrilZhao-sudo/tab-transformer
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
https://github.com/DevSinghSachan/unsupervised-passage-reranking
End-to-End Training of Neural Retrievers for Open-Domain Question Answering
https://github.com/HobbitLong/PyContrast
https://github.com/MS-P3/code4/tree/main/wukong
Wukong-Reader: Multi-modal Pre-training for Fine-grained Visual Document Understanding
https://github.com/MS-P3/code7/tree/main/wav2vec2_with_lm
https://github.com/MatteoZambra/SM_ML__MScThesis
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
https://github.com/MindSpore-scientific/code-11/tree/main/Least_Generative
Leveraging Pre-trained Checkpoints for Sequence Generation Tasks
https://github.com/Pointcept/Pointcept
PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding
https://github.com/ShadenSmith/ghpages-test
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
https://github.com/TRAILab/ST-SLidR
OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning
https://github.com/XavierSpycy/tabtransformers
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
https://github.com/YufeiHU-fr/obow_ssl
OBoW: Online Bag-of-Visual-Words Generation for Self-Supervised Learning
https://github.com/amazon-research/video-contrastive-learning
SeCo: Exploring Sequence Supervision for Unsupervised Representation Learning
https://github.com/anfreth/nampy
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
https://github.com/antoninofurnari/rulstm
Rolling-Unrolling LSTMs for Action Anticipation from First-Person Video
https://github.com/anushkayadav/Denoising_cifar10
Learning Deep Representations Using Convolutional Auto-encoders with Symmetric Skip Connections
https://github.com/applecrumble123/CVLR_pytorch
https://github.com/appleparan/mise.py
A Transformer-based Framework for Multivariate Time Series Representation Learning
https://github.com/aruberts/TabTransformerTF
TabTransformer: Tabular Data Modeling Using Contextual Embeddings
https://github.com/autonomousvision/unimatch
https://github.com/caskcsg/CoT-MAE
Drop your Decoder: Pre-training with Bag-of-Word Prediction for Dense Passage Retrieval
https://github.com/caskcsg/ir
Drop your Decoder: Pre-training with Bag-of-Word Prediction for Dense Passage Retrieval
https://github.com/cdoersch/deepcontext
Data-dependent Initializations of Convolutional Neural Networks
https://github.com/dpfried/rnng-bert
Multilingual Constituency Parsing with Self-Attention and Pre-Training
https://github.com/ducha-aiki/LSUVinit
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks
https://github.com/eastonYi/wav2vec
https://github.com/ed-fish/spatio-temporal-contrastive-film
https://github.com/ed-fish/spatio-temporal-contrastive-video
https://github.com/facebookresearch/CodeGen
DOBF: A Deobfuscation Pre-Training Objective for Programming Languages
https://github.com/facebookresearch/fairseq
Self-training and Pre-training are Complementary for Speech Recognition
https://github.com/floatingstarZ/GeRSP
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
https://github.com/floatingstarz/mutdet
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.