Check computer science papers: citations, claims and retractions

Predicting healthcare trajectories from medical records: a deep learning approach

Pham, T., Tran, T., Phung, D., & Venkatesh, S. (2017) · Journal of Biomedical Informatics

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 447

A new approach to signal classification using spectral correlation and neural networks

Fehske, A., Gaeddert, J., & Reed, J. H. (2005) · First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005.

Cognitive Radio Networks and Spectrum SensingWireless Signal Modulation Classification

Cited by 447

GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Ainslie, J., Lee-Thorp, J., de Jong, M., Zemlyanskiy, Y., Lebrón, F., & Sanghai, S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 447

Transfer learning for activity recognition: a survey

Cook, D., Feuz, K. D., & Krishnan, N. C. (2013) · Knowledge and Information Systems

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 447

Variational problems on flows of diffeomorphisms for image matching

Dupuis, P., Grenander, U., & Miller, M. I. (1998) · Quarterly of Applied Mathematics

Medical Image Segmentation TechniquesGeometric Analysis and Curvature Flows

Cited by 447

Ethics of AI-enabled recruiting and selection: a review and research agenda

Hunkenschroer, A. L., & Luetge, C. (2022) · Journal of Business Ethics

Ethics and Social Impacts of AIAI and HR Technologies

Cited by 447

Reinforcement learning and episodic memory in humans and animals: an integrative framework

Gershman, S. J., & Daw, N. D. (2017) · Annual Review of Psychology

Reinforcement Learning in RoboticsMemory and Neural Mechanisms

Cited by 446

GPTScore: Evaluate as You Desire

Fu, J., Ng, S.-K., Jiang, Z., & Liu, P. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 446

MaskGIT: Masked Generative Image Transformer

Chang, H., Zhang, H., Jiang, L., Liu, C., & Freeman, W. T. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 446

Data-efficient hierarchical reinforcement learning

Nachum, O., Gu, S., Lee, H., & Levine, S. (2018) · arXiv

Reinforcement Learning in RoboticsAI-based Problem Solving and Planning

Cited by 446

Reference Architectures for the Internet of Things

Weyrich, M., & Ebert, C. (2016) · IEEE Software

IoT and Edge/Fog ComputingDigital Transformation in Industry

Cited by 446

CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models

Nangia, N., Vania, C., Bhalerao, R., & Bowman, S. R. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Ethics and Social Impacts of AIHate Speech and Cyberbullying Detection

Cited by 446

Riemannian Manifold Learning

Lin, T., & Zha, H. (2008) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Face and Expression RecognitionTopological and Geometric Data Analysis

Cited by 446

Data cleaning: detecting, diagnosing, and editing data abnormalities

Van den Broeck, J., Argeseanu Cunningham, S., Eeckels, R., & Herbst, K. (2005) · PLoS Medicine

Data Quality and ManagementAnomaly Detection Techniques and Applications

Cited by 446

Artificial intelligence in histopathology: enhancing cancer research and clinical oncology

Shmatko, A., Ghaffari Laleh, N., Gerstung, M., & Kather, J. N. (2022) · Nature Cancer

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 446

Network Intrusion Detection Combined Hybrid Sampling With Deep Hierarchical Network

Jiang, K., Wang, W., Wang, A., & Wu, H. (2020) · IEEE Access

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 446

Transparency and accountability in AI systems: Safeguarding wellbeing in the age of algorithmic decision-making

Cheong, B. C. (2024) · Frontiers in Human Dynamics

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 445

Visual Dialog

Das, A., Kottur, S., Gupta, K., Singh, A., Yadav, D., Moura, J. M. F., Parikh, D., & Batra, D. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsSpeech and dialogue systems

Cited by 445

Autoregressive Image Generation using Residual Quantization

Lee, D., Kim, C., Kim, S., Cho, M., & Han, W.-S. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisAdvanced Neural Network Applications

Cited by 445

Deep multi-task learning with low level tasks supervised at lower layers

Søgaard, A., & Goldberg, Y. (2016) · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

Natural Language Processing TechniquesDomain Adaptation and Few-Shot Learning

Cited by 445

Generalized Autoencoder: A Neural Network Framework for Dimensionality Reduction

Wang, W., Huang, Y., Wang, Y., & Wang, L. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops

Face and Expression RecognitionNeural Networks and Applications

Cited by 445

Differential Privacy for Deep and Federated Learning: A Survey

Ouadrhiri, A. E., & Abdelhadi, A. (2022) · IEEE Access

Privacy-Preserving Technologies in DataCloud Data Security Solutions

Cited by 445

Reward is enough

Silver, D., Singh, S., Precup, D., & Sutton, R. S. (2021) · Artificial Intelligence

Reinforcement Learning in RoboticsPsychiatry, Mental Health, Neuroscience

Cited by 445

Security and Privacy Challenges of Large Language Models: A Survey

Das, B. C., Amini, M. H., & Wu, Y. (2025) · ACM Computing Surveys

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 445