Check computer science papers: citations, claims and retractions

Learning to Communicate with Deep Multi-Agent Reinforcement Learning

Foerster, J. N., Assael, Y. M., de Freitas, N., & Whiteson, S. (2016) · arXiv

Reinforcement Learning in RoboticsMulti-Agent Systems and Negotiation

Cited by 1,217

NMR techniques for quantum control and computation

Vandersypen, L. M. K., & Chuang, I. L. (2005) · Reviews of Modern Physics

Quantum Computing Algorithms and ArchitectureAdvanced NMR Techniques and Applications

Cited by 1,217

Advanced Encryption Standard (AES)

Heron, S. (2009) · Network Security

Cryptographic Implementations and SecurityCoding theory and cryptography

Cited by 1,216

Quantum computation and decision trees

Farhi, E., & Gutmann, S. (1998) · Physical Review A

Quantum Computing Algorithms and ArchitectureComplexity and Algorithms in Graphs

Cited by 1,215

Neural Network Acceptability Judgments

Warstadt, A., Singh, A., & Bowman, S. R. (2019) · Transactions of the Association for Computational Linguistics

Natural Language Processing TechniquesTopic Modeling

Cited by 1,215

FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Dao, T., Fu, D. Y., Ermon, S., Rudra, A., & Ré, C. (2022) · arXiv

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 1,214

Mastering Atari, Go, chess and shogi by planning with a learned model

Schrittwieser, J., Antonoglou, I., Hubert, T., Simonyan, K., Sifre, L., Schmitt, S., Guez, A., Lockhart, E., Hassabis, D., Graepel, T., et al. (2020) · Nature

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 1,214

Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

Schrittwieser, J., Antonoglou, I., Hubert, T., Simonyan, K., Sifre, L., Schmitt, S., Guez, A., Lockhart, E., Hassabis, D., Graepel, T., et al. (2019) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 1,214

Characterization of Encrypted and VPN Traffic using Time-related Features

Draper-Gil, G., Lashkari, A. H., Mamun, M. S. I., & A. Ghorbani, A. (2016) · Proceedings of the 2nd International Conference on Information Systems Security and Privacy

Internet Traffic Analysis and Secure E-votingNetwork Security and Intrusion Detection

Cited by 1,213

Monocular Pedestrian Detection: Survey and Experiments

Enzweiler, M., & Gavrila, D. M. (2009) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 1,213

Face X-Ray for More General Face Forgery Detection

Li, L., Bao, J., Zhang, T., Yang, H., Chen, D., Wen, F., & Guo, B. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionFace recognition and analysis

Cited by 1,211

Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent

Niu, F., Recht, B., Re, C., & Wright, S. J. (2011) · arXiv

Stochastic Gradient Optimization TechniquesParallel Computing and Optimization Techniques

Cited by 1,211

CNN-Generated Images Are Surprisingly Easy to Spot… for Now

Wang, S.-Y., Wang, O., Zhang, R., Owens, A., & Efros, A. A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 1,210

A Cross-Media Presence Questionnaire: The ITC-Sense of Presence Inventory

Lessiter, J., Freeman, J., Keogh, E., & Davidoff, J. (2001) · Presence: Teleoperators and Virtual Environments

Virtual Reality Applications and ImpactsFlow Experience in Various Fields

Cited by 1,208

Understanding and evaluating blind deconvolution algorithms

Levin, A., Weiss, Y., Durand, F., & Freeman, W. T. (2009) · 2009 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Image Processing TechniquesImage and Signal Denoising Methods

Cited by 1,208

Domain separation networks

Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., & Erhan, D. (2016) · arXiv

Domain Adaptation and Few-Shot LearningGenerative Adversarial Networks and Image Synthesis

Cited by 1,208

Siamese Instance Search for Tracking

Tao, R., Gavves, E., & Smeulders, A. W. M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,208

AI-Based Modeling: Techniques, Applications and Research Issues Towards Automation, Intelligent and Smart Systems

Sarker, I. H. (2022) · SN Computer Science

Artificial Intelligence ApplicationsInternet of Things and AI

Cited by 1,208

Don’t Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization

Narayan, S., Cohen, S. B., & Lapata, M. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Topic ModelingAdvanced Text Analysis Techniques

Cited by 1,207

The helmholtz machine

Dayan, P., Hinton, G. E., Neal, R. M., & Zemel, R. S. (1995) · Neural Computation

Neural Networks and ApplicationsBayesian Modeling and Causal Inference

Cited by 1,207

PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization

Zhang, J., Zhao, Y., Saleh, M., & Liu, P. J. (2019) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 1,206

Model Selection and Accounting for Model Uncertainty in Graphical Models Using Occam's Window

Madigan, D., & Raftery, A. E. (1994) · Journal of the American Statistical Association

Bayesian Modeling and Causal InferenceStatistical Methods and Inference

Cited by 1,205

Bias in computer systems

Friedman, B., & Nissenbaum, H. (1996) · ACM Transactions on Information Systems

Ethics and Social Impacts of AIInformation Systems Theories and Implementation

Cited by 1,203

Emotions Recognition Using EEG Signals: A Survey

Alarcao, S. M., & Fonseca, M. J. (2019) · IEEE Transactions on Affective Computing

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 1,201