https://github.com/shaoxiongji/awesome-knowledge-graph
A Review of Relational Machine Learning for Knowledge Graphs
Papers with Code 아카이브
BIG-bench Machine Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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This branch include most common machine learning fundamental algorithms.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/shap/shap
GPUTreeShap: Massively Parallel Exact Calculation of SHAP Scores for Tree Ensembles
https://github.com/shariff94/Facial_Keypoint_Detection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/sheetalreddy/Three-Approaches-for-Personalization-with-Applications-to-FederatedLearning
Three Approaches for Personalization with Applications to Federated Learning
https://github.com/shenweichen/DeepCTR
https://github.com/shenweichen/DeepCTR-Torch
https://github.com/sherkhan15/distarctor-Detection_Eyes_Emotions_CI
https://github.com/sheryl-ai/NeurIPS17-Competition-Classifying-Genetic-Mutations
A Multi-View Ensemble Classification Model for Clinically Actionable Genetic Mutations
https://github.com/shijiel2/cleverhans
https://github.com/shinjjo/MarsExpress
Machine learning for predicting thermal power consumption of the Mars Express Spacecraft
https://github.com/shinyingl/CV_Facial_Keypoints
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/shivamsaboo17/Deep-Restore-PyTorch
https://github.com/shizuo-kaji/PretrainCNNwithNoData
https://github.com/shreyas269/Pytorch-defensive-distillation
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
https://github.com/shriramsb/vdnn-plus-plus
vDNN: Virtualized Deep Neural Networks for Scalable, Memory-Efficient Neural Network Design
https://github.com/shrutimohanty/Hcodeep
Neuroevolution of Neural Network Architectures Using CoDeepNEAT and Keras
https://github.com/shuge-mit/mot_project
Near-linear time approximation algorithms for optimal transport via Sinkhorn iteration
https://github.com/shunk031/chainer-skin-lesion-detector
https://github.com/sid-sangal/RealTime
https://github.com/sidgautam95/adaptive-sampling-mri-suno
https://github.com/simonlousky/alteredAugmentor
Augmentor: An Image Augmentation Library for Machine Learning
https://github.com/simonsLiang/lettuce_paddle
https://github.com/simonwestberg/DD2412-Glow
https://github.com/simonwestberg/Glow
https://github.com/simplew2011/YOLO_ZOO
https://github.com/singh-ml/fsnet
FsNet: Feature Selection Network on High-dimensional Biological Data
https://github.com/siyangBai/twittering_sparkles
Our Practice Of Using Machine Learning To Recognize Species By Voice
https://github.com/skrantidatta/Attention-based-Skin-Cancer-Classification
https://github.com/skyve2012/DBA
Nuanced Metrics for Measuring Unintended Bias with Real Data for Text Classification
https://github.com/skywalk163/INFINITY
TorchMD: A deep learning framework for molecular simulations
https://github.com/sladewinter/ConvLSTM
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
https://github.com/slohani-ai/LG-OAM-simulations-with-Tensors
https://github.com/slundberg/esvalues
GPUTreeShap: Massively Parallel Exact Calculation of SHAP Scores for Tree Ensembles
https://github.com/slundberg/shap
GPUTreeShap: Massively Parallel Exact Calculation of SHAP Scores for Tree Ensembles
https://github.com/smazzanti/mrmr
https://github.com/smerdov/eSports_Sensors_Dataset
Detecting Video Game Player Burnout with the Use of Sensor Data and Machine Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.