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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/charan223/topology-conscious-networks

NiftyNet: a deep-learning platform for medical imaging

https://github.com/cheezzjazz/graph_nets

Relational inductive biases, deep learning, and graph networks

https://github.com/chenghui-666/acl

Co-Correcting: Noise-tolerant Medical Image Classification via mutual Label Correction

https://github.com/chenjiyan2001/paddle-FGCNN

Feature Generation by Convolutional Neural Network for Click-Through Rate Prediction

https://github.com/choicelab/grasping-invisible

A Deep Learning Approach to Grasping the Invisible

https://github.com/chongchen20/Deeplabcut

Deep learning tools for the measurement of animal behavior in neuroscience

https://github.com/chrischia06/AlgoTradingSimulatedPaths

Deep Learning for Portfolio Optimization

https://github.com/christianversloot/extra_keras_datasets

Deep Learning for Classical Japanese Literature

https://github.com/christianversloot/keras-cnn

Deep Learning for Classical Japanese Literature

https://github.com/chuxuantinh/PrivateDeepLearning-master-ct

Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning

https://github.com/cianmscannell/pinns

DeepXDE: A deep learning library for solving differential equations

https://github.com/cipnlu/InformationExtraction

A Survey of Deep Learning Methods for Relation Extraction

https://github.com/ckyeungac/DeepIRT

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

https://github.com/clairehester/face-mask-detector

Deep Learning Framework to Detect Face Masks from Video Footage

https://github.com/cleverhans-lab/cleverhans

The Limitations of Deep Learning in Adversarial Settings

https://github.com/cloneofsimo/poly2SOP

Deep Learning for Symbolic Mathematics

https://github.com/cobypenso/functional_ensemble_distillation

Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning

https://github.com/code-implementation1/Code4/tree/main/hed

HED-UNet: Combined Segmentation and Edge Detection for Monitoring the Antarctic Coastline

https://github.com/code-implementation1/Code9/tree/main/DeepText

Deep Learning with Differential Privacy

https://github.com/codlife/NLP

Wide & Deep Learning for Recommender Systems

https://github.com/coinse/sadl

Guiding Deep Learning System Testing using Surprise Adequacy

https://github.com/coloquinte/torchsr

Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network

https://github.com/cool21th/ai_drug_discovery

DeepCCI: End-to-end Deep Learning for Chemical-Chemical Interaction Prediction

https://github.com/copenlu/ALPS_2021

Visual Interaction with Deep Learning Models through Collaborative Semantic Inference

https://github.com/cor3bit/pde-solvers

DeepXDE: A deep learning library for solving differential equations

https://github.com/corail-research/learning-generic-csp

Graph Colouring Meets Deep Learning: Effective Graph Neural Network Models for Combinatorial Problems

https://github.com/coreylowman/ragz

Thinking Fast and Slow with Deep Learning and Tree Search

https://github.com/coreylowman/synthesis

Thinking Fast and Slow with Deep Learning and Tree Search

https://github.com/coryshain/dtsr

A Deep Learning Approach to Analyzing Continuous-Time Systems

https://github.com/cran/FuncNN

Deep Learning with Functional Inputs

https://github.com/cranial-xix/bome

BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach

https://github.com/crowdAI/crowdai-musical-genre-recognition-starter-kit

Xception: Deep Learning with Depthwise Separable Convolutions

https://github.com/cs-giung/course-dl-TP

Towards Deep Learning Models Resistant to Adversarial Attacks

https://github.com/csinva/local-vae

Interpretations are useful: penalizing explanations to align neural networks with prior knowledge

https://github.com/csxeba/Reproducing-Q-AGREL

A Biologically Plausible Learning Rule for Deep Learning in the Brain

https://github.com/ctcyang/horovod

Horovod: fast and easy distributed deep learning in TensorFlow

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