https://github.com/katerynaCh/Finnish-WW2-photographers-analysis
Machine Learning Based Analysis of Finnish World War II Photographers
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/kaustavsenkvs/Deep-Learning-Mini-Project
https://github.com/kavanp/MARCO
Classification of crystallization outcomes using deep convolutional neural networks
https://github.com/kclip/r_autoeval_plus
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
https://github.com/ken-power/CVND-FacialKeypointDetection
Facial Key Points Detection using Deep Convolutional Neural Network - NaimishNet
https://github.com/kenctrl/Differential-Privacy-2019
Differentially Private M-band Wavelet-Based Mechanisms in Machine Learning Environments
https://github.com/kentttttt/darknet
https://github.com/kevinkwshin/PaperList
https://github.com/khaamosh/Deep-Learning-Japanese-Character-Recognition
https://github.com/khanh-moriaty/DarknetAlexey
https://github.com/kherud/neural-additive-models-pt
Neural Additive Models: Interpretable Machine Learning with Neural Nets
https://github.com/kilimanj4r0/code-summarization-beyond-function-level
CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation
https://github.com/kingkonk81/cologne
https://github.com/kmamykin/askamanager_salary_survey
https://github.com/kmt112/probable-lamp
https://github.com/knowledge-technologies/fuji-score
https://github.com/kondukberna/Car_Detection
https://github.com/kooscii/badnets
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
https://github.com/kritiksoman/GIMP-ML
https://github.com/kubeflow/fate-operator
https://github.com/kubershahi/ashoka-secureml
https://github.com/kuronosec/arhuaco
A Security Monitoring Framework For Virtualization Based HEP Infrastructures
https://github.com/kurtisdavid/MetaOrthogonalization
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings
https://github.com/kushalsinha/AbbVie_FilterDryer_ARIMA_ML
A machine learning framework for computationally expensive transient models
https://github.com/kwantommy/breast-cancer-diagnosis
https://github.com/labelialabs/distributed-learning-contributivity
https://github.com/lacava/fair_gp
An Empirical Study of Rich Subgroup Fairness for Machine Learning
https://github.com/laclouis5/darknet2
https://github.com/lamalab-org/eval-cards
https://github.com/lanmei1211/face
https://github.com/lars-research/3d-pgt
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
https://github.com/laura-rieger/deep-explanation-penalization
Interpretable machine learning: definitions, methods, and applications
https://github.com/leandromineti/ml-curriculum
https://github.com/leandromineti/ml-knowledge-graph
https://github.com/learnables/learn2learn
https://github.com/lechengkong/oneforall
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.