Check computer science papers: citations, claims and retractions

Simulating Hamiltonian Dynamics with a Truncated Taylor Series

Berry, D. W., Childs, A. M., Cleve, R., Kothari, R., & Somma, R. D. (2015) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 742

Knowledge management in software engineering

Rus, I., & Lindvall, M. (2002) · IEEE Software

Software Engineering Techniques and PracticesKnowledge Management and Sharing

Cited by 742

Large-scale deep unsupervised learning using graphics processors

Raina, R., Madhavan, A., & Ng, A. Y. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning

Parallel Computing and Optimization TechniquesNeural Networks and Applications

Cited by 742

Discriminating Stress From Cognitive Load Using a Wearable EDA Device

Setz, C., Arnrich, B., Schumm, J., La Marca, R., Troster, G., & Ehlert, U. (2010) · IEEE Transactions on Information Technology in Biomedicine

Emotion and Mood RecognitionHeart Rate Variability and Autonomic Control

Cited by 742

3D Packing for Self-Supervised Monocular Depth Estimation

Guizilini, V., Ambrus, R., Pillai, S., Raventos, A., & Gaidon, A. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 741

Bias and Debias in Recommender System: A Survey and Future Directions

Chen, J., Dong, H., Wang, X., Feng, F., Wang, M., & He, X. (2023) · ACM Transactions on Information Systems

Recommender Systems and TechniquesEthics and Social Impacts of AI

Cited by 741

Rethinking the Inception Architecture for Computer Vision

Szegedy, C., Vanhoucke, V., Ioffe, S., Shlens, J., & Wojna, Z. (2015) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 741

Artificial evolution for computer graphics

Sims, K. (1991) · Proceedings of the 18th annual conference on Computer graphics and interactive techniques

Evolutionary Algorithms and ApplicationsComputer Graphics and Visualization Techniques

Cited by 741

Class-Incremental Learning: Survey and Performance Evaluation on Image Classification

Masana, M., Liu, X., Twardowski, B., Menta, M., Bagdanov, A. D., & van de Weijer, J. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 740

End-to-End Human Pose and Mesh Reconstruction with Transformers

Lin, K., Wang, L., & Liu, Z. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisHuman Pose and Action Recognition

Cited by 740

Learning Loss for Active Learning

Yoo, D., & Kweon, I. S. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Machine Learning and AlgorithmsDomain Adaptation and Few-Shot Learning

Cited by 740

Transition-Aware Human Activity Recognition Using Smartphones

Reyes-Ortiz, J.-L., Oneto, L., Samà, A., Parra, X., & Anguita, D. (2016) · Neurocomputing

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 740

On Defining Artificial Intelligence

Wang, P. (2019) · Journal of Artificial General Intelligence

Artificial Intelligence ApplicationsPsychiatry, Mental Health, Neuroscience

Cited by 740

Segmentation as selective search for object recognition

van de Sande, K. E. A., Uijlings, J. R. R., Gevers, T., & Smeulders, A. W. M. (2011) · 2011 International Conference on Computer Vision

Advanced Image and Video Retrieval TechniquesAdvanced Neural Network Applications

Cited by 739

BEAT: the Behavior Expression Animation Toolkit

Cassell, J., Vilhjálmsson, H. H., & Bickmore, T. (2001) · Proceedings of the 28th annual conference on Computer graphics and interactive techniques

Human Motion and AnimationSocial Robot Interaction and HRI

Cited by 739

Identifying facial phenotypes of genetic disorders using deep learning

Gurovich, Y., Hanani, Y., Bar, O., Nadav, G., Fleischer, N., Gelbman, D., Basel-Salmon, L., Krawitz, P. M., Kamphausen, S. B., Zenker, M., et al. (2019) · Nature Medicine

Face recognition and analysisGenomics and Rare Diseases

Cited by 739

Complexity and expressive power of logic programming

Dantsin, E., Eiter, T., Gottlob, G., & Voronkov, A. (2001) · ACM Computing Surveys

Logic, Reasoning, and KnowledgeAdvanced Graph Theory Research

Cited by 739

Effect of data encoding on the expressive power of variational quantum-machine-learning models

Schuld, M., Sweke, R., & Meyer, J. J. (2021) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 739

Medical Image Denoising Using Convolutional Denoising Autoencoders

Gondara, L. (2016) · 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)

Image and Signal Denoising MethodsImage Enhancement Techniques

Cited by 737

High-Resolution Image Synthesis with Latent Diffusion Models

Rombach, R., Blattmann, A., Lorenz, D., Esser, P., & Ommer, B. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 737

Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics

Lin, C.-Y., & Och, F. J. (2004) · Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics - ACL '04

Natural Language Processing TechniquesTranslation Studies and Practices

Cited by 737

Everybody Dance Now

Chan, C., Ginosar, S., Zhou, T., & Efros, A. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Generative Adversarial Networks and Image SynthesisHuman Motion and Animation

Cited by 737

PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation

Ansel, J., Yang, E., He, H., Gimelshein, N., Jain, A., Voznesensky, M., Bao, B., Bell, P., Berard, D., Burovski, E., et al. (2024) · Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2

Parallel Computing and Optimization TechniquesLogic, programming, and type systems

Cited by 737

Bayesian Computing with INLA: A Review

Rue, H., Riebler, A., Sørbye, S. H., Illian, J. B., Simpson, D. P., & Lindgren, F. K. (2017) · Annual Review of Statistics and Its Application

Gaussian Processes and Bayesian InferenceMarkov Chains and Monte Carlo Methods

Cited by 737