Papers with Code 아카이브

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평가표

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보존된 평가 기록

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코드

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

https://github.com/MartinTschechne/ML4H2020

ECG Heartbeat Classification: A Deep Transferable Representation

https://github.com/MarvinMartin24/MADA-PL

Domain-Adversarial Training of Neural Networks

https://github.com/MarvinTeichmann/KittiBox

MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving

https://github.com/MarvinTeichmann/KittiSeg

MultiNet: Real-time Joint Semantic Reasoning for Autonomous Driving

https://github.com/MasanoriYamada/Mine_pytorch

MINE: Mutual Information Neural Estimation

https://github.com/MashmallowWoR/AdversarialDeformation

ADef: an Iterative Algorithm to Construct Adversarial Deformations

https://github.com/Maskify/darknet

YOLO9000: Better, Faster, Stronger

https://github.com/MathiasStensrud/autoBleep

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/MathiasStensrud/capstone-2

Transfer Learning for Illustration Classification

https://github.com/Mattdl/CLsurvey

A continual learning survey: Defying forgetting in classification tasks

https://github.com/MatthewSZhang/ffs

Canonical-Correlation-Based Fast Feature Selection for Structural Health Monitoring

https://github.com/MatthieuCourbariaux/BinaryConnect

Neural Networks with Few Multiplications

https://github.com/Maveric4/pr19aaw01

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/MaxHolmberg96/GradCAM

Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization

https://github.com/MaxLikesMath/Barlow-Twins-Pytorch

Barlow Twins: Self-Supervised Learning via Redundancy Reduction

https://github.com/MaximIntegratedAI/ai8x-synthesis

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

https://github.com/MaximIntegratedAI/ai8x-training

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

https://github.com/Maxime-Jo/RF-Python

CatBoost: gradient boosting with categorical features support

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Fast_and_Accurate_Deep_Network_Learning_by_Exponential_Linear_Units_ELUs

Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs)

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Maxout_Networks

Maxout Networks

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Model_Agnostic_Meta_Learning_for_Fast_Adaptation_of_Deep_Networks

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks

https://github.com/MaximeVandegar/Papers-in-100-Lines-of-Code/tree/main/Network_In_Network

Network In Network

https://github.com/Maysir/GRCN

Revisiting Semi-Supervised Learning with Graph Embeddings

https://github.com/MayukhSobo/Conv4RNN

Convolutional Neural Networks for Sentence Classification

https://github.com/Mayurji/Image-Classification-PyTorch

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/McDonnell-Lab/1-bit-per-weight

Single-bit-per-weight deep convolutional neural networks without batch-normalization layers for embedded systems

https://github.com/Medabid1/Bayes-by-backprob

Weight Uncertainty in Neural Networks

https://github.com/Media-Smart/vedaseg

Bag of Tricks for Image Classification with Convolutional Neural Networks

https://github.com/Mees-Molenaar/protein_location

Universal Language Model Fine-tuning for Text Classification

https://github.com/Meghraj-Webllisto/stylegan

Very Deep Convolutional Networks for Large-Scale Image Recognition

https://github.com/MehdiChelh/Zoo

Weight Uncertainty in Neural Networks

https://github.com/MehdiZouitine/Learning-Disentangled-Representations-via-Mutual-Information-Estimation

Learning Disentangled Representations via Mutual Information Estimation

https://github.com/Meowuu7/Point-Transformer

Point Transformer

https://github.com/MhYao2014/HyperbolicEmbedding

Bag of Tricks for Efficient Text Classification

https://github.com/MichSchli/RelationPrediction

Modeling Relational Data with Graph Convolutional Networks

https://github.com/MichaelIcaza/localization-from-image-labels

Patch-based Convolutional Neural Network for Whole Slide Tissue Image Classification

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