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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/yizhe-ang/fake-detection-lab

Adversarial Attack on Deep Learning-Based Splice Localization

https://github.com/ykiiiiii/CornealAI

Deep Learning Based Unsupervised and Semi-supervised Classification for Keratoconus

https://github.com/yorkerlin/remove-the-square-root

On Empirical Comparisons of Optimizers for Deep Learning

https://github.com/yuanl12/tda_updating_persistence

A Topology Layer for Machine Learning

https://github.com/yufeiwu1011/Robust-Amortized-Bayesian-Inference

A Deep Learning Method for Comparing Bayesian Hierarchical Models

https://github.com/yule-buaa/dyglib

Temporal Graph Networks for Deep Learning on Dynamic Graphs

https://github.com/yuliytsank/glaucoma-project

A feature agnostic approach for glaucoma detection in OCT volumes

https://github.com/yytyvonne/DQN_agent_Chatbot

Deep Reinforcement Learning for Conversational AI

https://github.com/zaabl/Arabic-Optical-Character-Recognizer

Deep Learning Autoencoder Approach for Handwritten Arabic Digits Recognition

https://github.com/zabaras/deep-turbulence

Multi-fidelity Generative Deep Learning Turbulent Flows

https://github.com/zachzhu2016/Spectraface

Face Recognition: From Traditional to Deep Learning Methods

https://github.com/zachzhu2016/thermal-face-recognition

Face Recognition: From Traditional to Deep Learning Methods

https://github.com/zamanzadeh/CARLA

Deep Learning for Time Series Anomaly Detection: A Survey

https://github.com/zghera/pvcnn-tf

Point-Voxel CNN for Efficient 3D Deep Learning

https://github.com/zghera/voxel-tf-ops

Point-Voxel CNN for Efficient 3D Deep Learning

https://github.com/zhanglab-aim/cancer-net

Relational inductive biases, deep learning, and graph networks

https://github.com/zhangyaoyuan/GAN-Simplification

A Theoretically Grounded Application of Dropout in Recurrent Neural Networks

https://github.com/zhangyongshun/BagofTricks-LT

Identifying and Compensating for Feature Deviation in Imbalanced Deep Learning

https://github.com/zhangyuwangumass/Trajectory-Reweighted-Sampler

Learning to Reweight Examples for Robust Deep Learning

https://github.com/zhaolongkzz/human_motion

Structural-RNN: Deep Learning on Spatio-Temporal Graphs

https://github.com/zhileichen99/utopic

RPM-Net: Robust Point Matching using Learned Features

https://github.com/zhonghual1206/bertcpu

Horovod: fast and easy distributed deep learning in TensorFlow

https://github.com/zhonghual1206/horvodval

Horovod: fast and easy distributed deep learning in TensorFlow

https://github.com/zhoudoao-bayes/tf-probability

TensorFlow Distributions

https://github.com/zhusiling/UNets

Enforcing temporal consistency in Deep Learning segmentation of brain MR images

https://github.com/zibojia/rslad

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/ziliat-nask/stylometrix

StyloMetrix: An Open-Source Multilingual Tool for Representing Stylometric Vectors

https://github.com/zion-king/Deep-Learning-for-Person-Re-identification

Deep Learning for Person Re-identification: A Survey and Outlook

https://github.com/zitongyu/flex-modal-fas

Deep Learning for Face Anti-Spoofing: A Survey

https://github.com/zjfheart/Friendly-Adversarial-Training

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/zotrick/Pneumonia_classification_Xception

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/zouhanrui/2dunet

Efficient and accurate inversion of multiple scattering with deep learning

https://github.com/zouhanrui/mri

Efficient and accurate inversion of multiple scattering with deep learning

https://github.com/zzzace2000/dropout-feature-ranking

Dropout Feature Ranking for Deep Learning Models

https://github.com/zzzer1019/FL_DP

Deep Learning with Differential Privacy

https://gitlab.com/Skelp/aptx

APTx: better activation function than MISH, SWISH, and ReLU's variants used in deep learning

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