Check computer science papers: citations, claims and retractions

The effects of integrating mobile devices with teaching and learning on students' learning performance: A meta-analysis and research synthesis

Sung, Y.-T., Chang, K.-E., & Liu, T.-C. (2016) · Computers & Education

Mobile Learning in EducationInnovative Teaching and Learning Methods

Cited by 1,574

Deep learning enables rapid identification of potent DDR1 kinase inhibitors

Zhavoronkov, A., Ivanenkov, Y. A., Aliper, A., Veselov, M. S., Aladinskiy, V. A., Aladinskaya, A. V., Terentiev, V. A., Polykovskiy, D. A., Kuznetsov, M. D., Asadulaev, A., et al. (2019) · Nature Biotechnology

Computational Drug Discovery MethodsMachine Learning in Materials Science

Cited by 1,573

Toward Open Set Recognition

Scheirer, W. J., de Rezende Rocha, A., Sapkota, A., & Boult, T. E. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,573

Coase's penguin, or, linux and “the nature of the firm”

Benkler, Y. (2002) · The Yale Law Journal

Open Source Software InnovationsEconomic Theory and Institutions

Cited by 1,572

Some practical considerations and applications of the national cancer institute in vitro anticancer drug discovery screen

Boyd, M. R., & Paull, K. D. (1995) · Drug Development Research

Computational Drug Discovery MethodsCancer therapeutics and mechanisms

Cited by 1,572

ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification

Desplanques, B., Thienpondt, J., & Demuynck, K. (2020) · Interspeech 2020

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 1,568

Topic-sensitive PageRank

Haveliwala, T. H. (2002) · Proceedings of the 11th international conference on World Wide Web

Information Retrieval and Search BehaviorWeb Data Mining and Analysis

Cited by 1,567

The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systematic review

Zhai, C., Wibowo, S., & Li, L. D. (2024) · Smart Learning Environments

Artificial Intelligence in EducationEthics and Social Impacts of AI

Cited by 1,567

Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing

Li, H., Ota, K., & Dong, M. (2018) · IEEE Network

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 1,566

Federated Optimization: Distributed Machine Learning for On-Device Intelligence

Konečný, J., McMahan, H. B., Ramage, D., & Richtárik, P. (2016) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 1,563

SemEval-2017 Task 1: Semantic Textual Similarity Multilingual and Crosslingual Focused Evaluation

Cer, D., Diab, M., Agirre, E., Lopez-Gazpio, I., & Specia, L. (2017) · Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)

Topic ModelingNatural Language Processing Techniques

Cited by 1,562

Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Jacot, A., Gabriel, F., & Hongler, C. (2018) · arXiv

Gaussian Processes and Bayesian InferenceNeural Networks and Applications

Cited by 1,562

Towards a general-purpose foundation model for computational pathology

Chen, R. J., Ding, T., Lu, M. Y., Williamson, D. F. K., Jaume, G., Song, A. H., Chen, B., Zhang, A., Shao, D., Shaban, M., et al. (2024) · Nature Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 1,560

Theoretically principled trade-off between robustness and accuracy

Zhang, H., Yu, Y., Jiao, J., Xing, E. P., Ghaoui, L. E., & Jordan, M. I. (2019) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1,560

Quantum Chemistry in the Age of Quantum Computing

Cao, Y., Romero, J., Olson, J. P., Degroote, M., Johnson, P. D., Kieferová, M., Kivlichan, I. D., Menke, T., Peropadre, B., Sawaya, N. P. D., et al. (2019) · Chemical Reviews

Quantum Computing Algorithms and ArchitectureAdvanced Chemical Physics Studies

Cited by 1,560

Convolutional neural networks at constrained time cost

He, K., & Sun, J. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,558

Top-down versus bottom-up attentional control: a failed theoretical dichotomy

Awh, E., Belopolsky, A. V., & Theeuwes, J. (2012) · Trends in Cognitive Sciences

Visual Attention and Saliency DetectionNeural and Behavioral Psychology Studies

Cited by 1,557

Neuroscience-Inspired Artificial Intelligence

Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017) · Neuron

Neural Networks and ApplicationsCognitive Computing and Networks

Cited by 1,557

Flamingo: a Visual Language Model for Few-Shot Learning

Alayrac, J.-B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al. (2022) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,555

Fast Online Object Tracking and Segmentation: A Unifying Approach

Wang, Q., Zhang, L., Bertinetto, L., Hu, W., & Torr, P. H. S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,554

Persuasive technology: using computers to change what we think and do

Fogg, B. J. (2002) · Ubiquity

Innovative Human-Technology InteractionInformation Systems Theories and Implementation

Cited by 1,554

Dataset Shift in Machine Learning

(2008) · The MIT Press eBooks

Domain Adaptation and Few-Shot LearningMachine Learning and Algorithms

Cited by 1,553

Enhancing geometric factors in model learning and inference for object detection and instance segmentation

Zheng, Z., Wang, P., Ren, D., Liu, W., Ye, R., Hu, Q., & Zuo, W. (2022) · IEEE Transactions on Cybernetics

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,552

A primer in BERTology: What we know about how BERT works

Rogers, A., Kovaleva, O., & Rumshisky, A. (2020) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 1,552