https://github.com/AnabelSMRuggiero/Dimensionality-Reduction-Tutorial
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Papers with Code 아카이브
BIG-bench Machine Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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- 보존된 평가 기록
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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/Anaststam/Facial-Keypoints-detection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/AndreyBychkov/QBee
Learning physics-based reduced-order models for a single-injector combustion process
https://github.com/AngelDrt/aiProject
Lung and Colon Cancer Histopathological Image Dataset (LC25000)
https://github.com/AngeloManzatto/FacialKeypoints
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/AngusG/cleverhans-attacking-bnns
https://github.com/AnneDirkson/FuzzyBIO
https://github.com/ArashRahnama/Adversarial-Explainations-for-Artificial-Intelligence-systems-AXAI
An Adversarial Approach for Explaining the Predictions of Deep Neural Networks
https://github.com/ArashRahnama/Adversarial-Explanations-for-Artificial-Intelligence-Systems-AXAI
An Adversarial Approach for Explaining the Predictions of Deep Neural Networks
https://github.com/Argaadya/intro-bayesian
Practical Bayesian Optimization of Machine Learning Algorithms
https://github.com/AriChow/error_propagation
https://github.com/Arpan-Mishra/Selfie-Filter-Project
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/AryaKoureshi/Magnocellular-Parvocellular-Coactivation-Task-in-MATLAB
DysLexML: Screening Tool for Dyslexia Using Machine Learning
https://github.com/Ashish-Sankritya/darknet_CNN
https://github.com/AshwinRJ/Federated-Learning-PyTorch
https://github.com/AstraZeneca/awesome-shapley-value
https://github.com/Atharva-Phatak/One-Shot-Art
Generalizing from a Few Examples: A Survey on Few-Shot Learning
https://github.com/AudreyBeard/Datasheets-for-Datasets-Template
https://github.com/Automunge/AutoMunge
https://github.com/Avmb/semantic_neq_game
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
https://github.com/AwesumMe/RetailClassification
https://github.com/BNN-UPC/MARL-GNN-TE
Is Machine Learning Ready for Traffic Engineering Optimization?
https://github.com/BRAIN-chain/FRAIN
https://github.com/BabafemiOyinlola/Predicting-and-Analyzing-Law-Making-in-Kenya
https://github.com/BenjiKCF/SNN-with-embeddings-for-Malware-Prediction
https://github.com/BerkeleyLearnVerify/VerifAI
VERIFAI: A Toolkit for the Design and Analysis of Artificial Intelligence-Based Systems
https://github.com/Bhushan-Jagtap-2013/Adversarial_Attack_on_RNN
Crafting Adversarial Input Sequences for Recurrent Neural Networks
https://github.com/BielStela/membership_inference
Understanding Membership Inferences on Well-Generalized Learning Models
https://github.com/BioImageInformatics/tfmodels
https://github.com/Boluwatifeh/Secure-AI
https://github.com/BouchardLab/pylearn2
https://github.com/BruceBinBoxing/Deep_Learning_Weather_Forecasting
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
https://github.com/BruceBinBoxing/WF
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
https://github.com/BruceBinBoxing/Weather_Forecasting
Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting
https://github.com/Buffoni/fourier_learning
https://github.com/Burf/tfdetection
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.