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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/AntoBr96/CNN-LSTM_Limit_Order_Book

Deep Learning modeling of Limit Order Book: a comparative perspective

https://github.com/Arko98/A-Deep-Learning-Approach-for-Automatic-Detection-of-Fake-News

A Deep Learning Approach for Automatic Detection of Fake News

https://github.com/ArrasL/LRP_for_LSTM

Analyzing Neuroimaging Data Through Recurrent Deep Learning Models

https://github.com/ArturGoldman/NN_DE_solver

DGM: A deep learning algorithm for solving partial differential equations

https://github.com/AshwinRJ/Federated-Learning-PyTorch

Deep Learning with Differential Privacy

https://github.com/AthanasiosRaptakis/Deep-Learning-for-Physical-Processes

Deep Learning for Physical Processes: Incorporating Prior Scientific Knowledge

https://github.com/AvivNavon/AuxiLearn

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

https://github.com/Ayaanesmail/Test.-

Deep learning tools for the measurement of animal behavior in neuroscience

https://github.com/Azure/AzureChestXRay

Boosted Cascaded Convnets for Multilabel Classification of Thoracic Diseases in Chest Radiographs

https://github.com/BRAIN-chain/FRAIN

Deep Learning with Differential Privacy

https://github.com/BathVisArtData/PeopleArt

The Cross-Depiction Problem: Computer Vision Algorithms for Recognising Objects in Artwork and in Photographs

https://github.com/Berenice2018/PySyft-Bc

A generic framework for privacy preserving deep learning

https://github.com/BobLd/DocumentLayoutAnalysis

LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

https://github.com/BochaoJ-Lilly/InceptionTime

InceptionTime: Finding AlexNet for Time Series Classification

https://github.com/BojanFaletic/IQ_net

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

https://github.com/BrianYang2013/JHU_AI_Journey

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

https://github.com/Bunseki2/DeepL

Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models

https://github.com/C0sch0/lecturasIIC3633-2021

Deep Learning based Recommender System: A Survey and New Perspectives

https://github.com/COMP6248-Reproducability-Challenge/NODE_FOR_DL_ON_TABULAR_DATA

Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data

https://github.com/COMPUTE-LU/AI4MedLife_imaging_2021

3D Deep Learning on Medical Images: A Review

https://github.com/CVRL/iris-recognition-OTS-DNN

Iris Recognition with Image Segmentation Employing Retrained Off-the-Shelf Deep Neural Networks

https://github.com/CXMANDTXW/MTL-Using-Uncertainty-to-Weigh-Losses

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

https://github.com/Cadden/paddle-adver

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/Candice-X/w-net-for-image-segmentation

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/CarloLucibello/GraphNeuralNetworks.jl

GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia

https://github.com/CarstenIsert/DeepBurn

A Mobile App for Wound Localization using Deep Learning

https://github.com/Chan-Li/SAS-model

Learning credit assignment

https://github.com/CharlieSergeant/pollen

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/ChenDelong1999/HHForecasting

Significant Wave Height Prediction based on Wavelet Graph Neural Network

https://github.com/ChenLiu-1996/DiffusionSpectralEntropy

Deep Learning and the Information Bottleneck Principle

https://github.com/ChengzeYe/Defrise-and-Clack-reconstruction

Deep Learning Computed Tomography based on the Defrise and Clack Algorithm

https://github.com/ChrisCummins/phd

ProGraML: Graph-based Deep Learning for Program Optimization and Analysis

https://github.com/ChrisWaites/pyvacy

Deep Learning with Differential Privacy

https://github.com/ChristianMarzahl/ObjectDetection

Deep Learning-Based Quantification of Pulmonary Hemosiderophages in Cytology Slides

https://github.com/ChrominskiMateusz/LSTM_layer_with_kernel_fusion

The Matrix Calculus You Need For Deep Learning

https://github.com/ClaraGalimberti/HamiltonianNet

Stable Architectures for Deep Neural Networks

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