Check computer science papers: citations, claims and retractions

Non-local Neural Networks

Wang, X., Girshick, R., Gupta, A., & He, K. (2017) · arXiv

Advanced Neural Network ApplicationsHuman Pose and Action Recognition

Cited by 11,689

Anomaly detection: A survey

Chandola, V., Banerjee, A., & Kumar, V. (2009) · ACM Computing Surveys

Anomaly Detection Techniques and ApplicationsSoftware System Performance and Reliability

Cited by 11,687

Gephi: An Open Source Software for Exploring and Manipulating Networks

Bastian, M., Heymann, S., & Jacomy, M. (2009) · Proceedings of the International AAAI Conference on Web and Social Media

Data Visualization and AnalyticsComplex Network Analysis Techniques

Cited by 11,675

Causality: Models, Reasoning, and Inference

Pearl, J. (2009) · Cambridge University Press eBooks

Bayesian Modeling and Causal InferenceAdvanced Causal Inference Techniques

Cited by 11,653

Non-local Neural Networks

Wang, X., Girshick, R., Gupta, A., & He, K. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsHuman Pose and Action Recognition

Cited by 11,596

Learning Deep Features for Discriminative Localization

Zhou, B., Khosla, A., Lapedriza, A., Oliva, A., & Torralba, A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 11,428

Classification And Regression Trees

Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · Routledge eBooks

Data Mining Algorithms and ApplicationsStatistical Methods and Inference

Cited by 11,417

An Introduction to Genetic Algorithms

Mitchell, M. (1996) · The MIT Press eBooks

Evolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms Research

Cited by 11,340

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI

Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., Benjamins, R., et al. (2019) · arXiv

Explainable Artificial Intelligence (XAI)Ethics and Social Impacts of AI

Cited by 11,321

Introduction to Information Retrieval

Manning, C. D., Raghavan, P., & Schütze, H. (2008) · Cambridge University Press eBooks

Information Retrieval and Search BehaviorAlgorithms and Data Compression

Cited by 11,288

Finding structure in time

Elman, J. L. (1990) · Cognitive Science

Neural Networks and ApplicationsNeurobiology of Language and Bilingualism

Cited by 11,212

Caffe: Convolutional Architecture for Fast Feature Embedding

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · Proceedings of the 22nd ACM international conference on Multimedia

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 11,077

ORB: An efficient alternative to SIFT or SURF

Rublee, E., Rabaud, V., Konolige, K., & Bradski, G. (2011) · 2011 International Conference on Computer Vision

Advanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

Cited by 11,037

Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling

Chung, J., Gulcehre, C., Cho, K., & Bengio, Y. (2014) · arXiv

Neural Networks and ApplicationsSpeech Recognition and Synthesis

Cited by 11,008

A Comprehensive Survey on Graph Neural Networks

Wu, Z., Pan, S., Chen, F., Long, G., Zhang, C., & Yu, P. S. (2021) · IEEE Transactions on Neural Networks and Learning Systems

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 11,000

Finite Mixture Models

McLachlan, G., & Peel, D. (2000) · Wiley Series in Probability and Statistics

Bayesian Methods and Mixture ModelsAdvanced Clustering Algorithms Research

Cited by 10,991

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Raffel, C., Shazeer, N., Roberts, A., Lee, K., Narang, S., Matena, M., Zhou, Y., Li, W., & Liu, P. J. (2019) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 10,929

node2vec: Scalable Feature Learning for Networks

Grover, A., & Leskovec, J. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 10,926

A Study of Cross-Validation and Bootstrap for Accuracy Estimation and Model Selection

Kohavi, R. (1995) · Zenodo

Machine Learning and Data ClassificationData Mining and Machine Learning Applications

Cited by 10,909

A simple framework for contrastive learning of visual representations

Chen, T., Kornblith, S., Norouzi, M., & Hinton, G. (2020) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 10,857

Continuous control with deep reinforcement learning

Lillicrap, T. P., Hunt, J. J., Pritzel, A., Heess, N., Erez, T., Tassa, Y., Silver, D., & Wierstra, D. (2015) · arXiv

Reinforcement Learning in RoboticsAdaptive Dynamic Programming Control

Cited by 10,782

Quantum cryptography based on Bell’s theorem

Ekert, A. K. (1991) · Physical Review Letters

Quantum Information and CryptographyQuantum Mechanics and Applications

Cited by 10,777

Identity Mappings in Deep Residual Networks

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 10,665

Inductive Representation Learning on Large Graphs

Hamilton, W. L., Ying, R., & Leskovec, J. (2017) · arXiv

Advanced Graph Neural NetworksComplex Network Analysis Techniques

Cited by 10,639