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Deep Learning

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

https://github.com/Sempronius/LITS_test

Detection-aided liver lesion segmentation using deep learning

https://github.com/SensongAn/Meta-atoms-data-sharing

A Freeform Dielectric Metasurface Modeling Approach Based on Deep Neural Networks

https://github.com/SeptivianaSavitri/adl_python

Autonomous Deep Learning: Continual Learning Approach for Dynamic Environments

https://github.com/SeverTopan/SATNet

SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver

https://github.com/Sharad24/Epileptic-Seizure-Detection

Learning Robust Features using Deep Learning for Automatic Seizure Detection

https://github.com/SharadGitHub/Self-Supervised-Autoencoder

Multi-Task Learning Using Uncertainty to Weigh Losses for Scene Geometry and Semantics

https://github.com/ShashankMasade/major-project

Using Deep Learning for Image-Based Plant Disease Detection

https://github.com/Sherrylife/Local-Differential-Privacy-for-Deep-Learning

Local Differential Privacy for Deep Learning

https://github.com/Shesh6/Deep-Renormalization

An exact mapping between the Variational Renormalization Group and Deep Learning

https://github.com/ShiqiYu/libfacedetection

Detect Faces Efficiently: A Survey and Evaluations

https://github.com/ShubhayanS/Multiclass-Diabetic-Retinopathy-Detection

Transfer Learning based Detection of Diabetic Retinopathy from Small Dataset

https://github.com/SimonKoppers/DELIMIT

DELIMIT PyTorch - An extension for Deep Learning in Diffusion Imaging

https://github.com/SindhuMadi/FakeNewsDetection

Fake news detection using Deep Learning

https://github.com/Sorananakiii/Fine-grained-image-recognition

Deep Learning for Fine-Grained Image Analysis: A Survey

https://github.com/SparkyAndy/XCS229ii-FinalProject

DeepTaskAPT: Insider APT detection using Task-tree based Deep Learning

https://github.com/StatsDLMathsRecomSys/Self-attention-with-Functional-Time-Representation-Learning

A Temporal Kernel Approach for Deep Learning with Continuous-time Information

https://github.com/StephenBo-China/DIEN

Deep Interest Evolution Network for Click-Through Rate Prediction

https://github.com/StephenBo-China/DIEN-DIN

Deep Interest Evolution Network for Click-Through Rate Prediction

https://github.com/StephenBo-China/recommendation_system_sort_model

Deep Interest Evolution Network for Click-Through Rate Prediction

https://github.com/Sudhir11292rt/City-scale-Road-Audit

City-Scale Road Audit System using Deep Learning

https://github.com/SunChenxiSCX/ISMTS-Review

A Review of Deep Learning Methods for Irregularly Sampled Medical Time Series Data

https://github.com/SuperKam91/bnn

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

https://github.com/T-Almeida/tensorflow-keras-multidimensional-rnn

DeepRank: A New Deep Architecture for Relevance Ranking in Information Retrieval

https://github.com/TCIPrime/turbo-nn

Communication Algorithms via Deep Learning

https://github.com/TQCAI/graph_nets_pytorch

Relational inductive biases, deep learning, and graph networks

https://github.com/TanyaChutani/Xception-Tf2.0

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/Tarkiyah/HackingNeuralNetwork

Hacking Neural Networks: A Short Introduction

https://github.com/Tarkiyah/kaotlin

Kaolin: A PyTorch Library for Accelerating 3D Deep Learning Research

https://github.com/Tenavi/HJB_NN

Adaptive Deep Learning for High-Dimensional Hamilton-Jacobi-Bellman Equations

https://github.com/Tencent/tencent-ml-images

Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

https://github.com/TestSelection/TestSelection

Guiding Deep Learning System Testing using Surprise Adequacy

https://github.com/TheMrGhostman/InceptionTime-Pytorch

InceptionTime: Finding AlexNet for Time Series Classification

https://github.com/TheMrGhostman/InceptionTime-for-VAE-Pytorch

InceptionTime: Finding AlexNet for Time Series Classification

https://github.com/TheSaintIndiano/Bamboo-Forest-Detection

Deep Learning for Identifying Metastatic Breast Cancer

https://github.com/TheoryDev/Deep-neural-network-training-optimisation

Stable Architectures for Deep Neural Networks

https://github.com/Thinklab-SJTU/ThinkMatch

Deep Graph Matching via Blackbox Differentiation of Combinatorial Solvers

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