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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/jdxyw/deepKT

Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory

https://github.com/jefffffffu/dpsur

Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning

https://github.com/jegarcian/hep-ml

Application of a Convolutional Neural Network for image classification to the analysis of collisions in High Energy Physics

https://github.com/jesperhauch/polynomial_deep_learning

Deep Polynomial Neural Networks

https://github.com/jessearodriguez/LJ-Audio-dataset-generator

Exploring Transfer Learning for Low Resource Emotional TTS

https://github.com/jessemzhang/dl_spectral_normalization

Understanding deep learning requires rethinking generalization

https://github.com/jiahuei/COMIC-Compact-Image-Captioning-with-Attention

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

https://github.com/jiahuei/COMIC-Towards-A-Compact-Image-Captioning-Model-with-Attention

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

https://github.com/jiajunhua/yanshengjia-ml-road

Notes on Deep Learning for NLP

https://github.com/jiean001/models_m/tree/main/DIEN

Deep Interest Evolution Network for Click-Through Rate Prediction

https://github.com/jim-schwoebel/allie

Ludwig: a type-based declarative deep learning toolbox

https://github.com/jindongwang/deep-learning-activity-recognition

Deep Learning for Sensor-based Activity Recognition: A Survey

https://github.com/jingpeilu/psmnet_ros

SuPer Deep: A Surgical Perception Framework for Robotic Tissue Manipulation using Deep Learning for Feature Extraction

https://github.com/jinliangwei/tensor2tensor-1.11

Tensor2Tensor for Neural Machine Translation

https://github.com/jlianglab/CAD_PE

Seeking an Optimal Approach for Computer-Aided Pulmonary Embolism Detection

https://github.com/jloveric/high-order-layers-torch

Discontinuous Piecewise Polynomial Neural Networks

https://github.com/jlrussin/syntactic_attention

Compositional generalization in a deep seq2seq model by separating syntax and semantics

https://github.com/jnan1/FlowVerify

Combining Deep Learning and Verification for Precise Object Instance Detection

https://github.com/joan-teriihoania/algorithme-genetique

Deep Learning with Darwin: Evolutionary Synthesis of Deep Neural Networks

https://github.com/joelweber97/Python3_TF_Certificate

A guide to convolution arithmetic for deep learning

https://github.com/joernio/joernti-codetidal5

Advanced Graph-Based Deep Learning for Probabilistic Type Inference

https://github.com/johanattia/tensorflow-saint

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

https://github.com/johnb110/vdpython

VulDeePecker: A Deep Learning-Based System for Vulnerability Detection

https://github.com/johnhernandez3/VANGOGHS-EAR

Deep Learning for Audio Signal Processing

https://github.com/johnsonkee/graduate_design

The Limitations of Deep Learning in Adversarial Settings

https://github.com/jongcye/Domain.Adaptation.AcceleratedMR

Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MR

https://github.com/jordanott/CBRAIN-CAM

Deep learning to represent sub-grid processes in climate models

https://github.com/josephdviviano/lstm-variational-dropout

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

https://github.com/jrzaurin/pytorch-widedeep

SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training

https://github.com/jsleroux/Recommender-Systems

Wide & Deep Learning for Recommender Systems

https://github.com/jsun1/CS230Project

Deep Learning for Predicting Asset Returns

https://github.com/julianbertini/MSNet

NiftyNet: a deep-learning platform for medical imaging

https://github.com/jun-cen/psl

Evidential Deep Learning to Quantify Classification Uncertainty

https://github.com/junbinhuang/DeepRitz

DGM: A deep learning algorithm for solving partial differential equations

https://github.com/jwzhanggy/Graph-Bert

SEGEN: Sample-Ensemble Genetic Evolutional Network Model

https://github.com/jx-zhong-for-academic-purpose/kinet

MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences

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