Check computer science papers: citations, claims and retractions

Measurement optimization in the variational quantum eigensolver using a minimum clique cover

Verteletskyi, V., Yen, T.-C., & Izmaylov, A. F. (2020) · The Journal of Chemical Physics

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 269

Deep reinforcement learning and its neuroscientific implications

Botvinick, M., Wang, J. X., Dabney, W., Miller, K. J., & Kurth-Nelson, Z. (2020) · Neuron

Reinforcement Learning in RoboticsNeural and Behavioral Psychology Studies

Cited by 269

Cross-Task Generalization via Natural Language Crowdsourcing Instructions

Mishra, S., Khashabi, D., Baral, C., & Hajishirzi, H. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 269

BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains

Labrak, Y., Bazoge, A., Morin, E., Gourraud, P.-A., Rouvier, M., & Dufour, R. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 269

Warm-starting quantum optimization

Egger, D. J., Mareček, J., & Woerner, S. (2021) · Quantum

Quantum Computing Algorithms and ArchitectureComplexity and Algorithms in Graphs

Cited by 269

Cross-Task Generalization via Natural Language Crowdsourcing Instructions

Mishra, S., Khashabi, D., Baral, C., & Hajishirzi, H. (2021) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 269

A High-Level Overview of AI Ethics

Kazim, E., & Koshiyama, A. (2020) · SSRN Electronic Journal

Ethics and Social Impacts of AIEthics in Business and Education

Cited by 269

Query-Efficient Hard-label Black-box Attack:An Optimization-based Approach

Cheng, M., Le, T., Chen, P.-Y., Yi, J., Zhang, H., & Hsieh, C.-J. (2018) · arXiv

Adversarial Robustness in Machine LearningSoftware Testing and Debugging Techniques

Cited by 269

PopBots: Designing an Artificial Intelligence Curriculum for Early Childhood Education

Williams, R., Park, H. W., Oh, L., & Breazeal, C. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Teaching and Learning ProgrammingEducational Robotics and Engineering

Cited by 269

A high-level overview of AI ethics

Kazim, E., & Koshiyama, A. S. (2021) · Patterns

Ethics and Social Impacts of AIEthics in Business and Education

Cited by 269

SAE+LSTM: A New Framework for Emotion Recognition From Multi-Channel EEG

Xing, X., Li, Z., Xu, T., Shu, L., Hu, B., & Xu, X. (2019) · Frontiers in Neurorobotics

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 269

Combining structured and unstructured data for predictive models: a deep learning approach

Zhang, D., Yin, C., Zeng, J., Yuan, X., & Zhang, P. (2020) · BMC Medical Informatics and Decision Making

Machine Learning in HealthcareNursing Diagnosis and Documentation

Cited by 269

Explainable Artificial Intelligence: a Systematic Review

Vilone, G., & Longo, L. (2020) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 269

Trends in AI inference energy consumption: Beyond the performance-vs-parameter laws of deep learning

Desislavov, R., Martínez-Plumed, F., & Hernández-Orallo, J. (2023) · Sustainable Computing: Informatics and Systems

Advanced Neural Network ApplicationsAdversarial Robustness in Machine Learning

Cited by 269

Efficient networks for quantum factoring

Beckman, D., Chari, A. N., Devabhaktuni, S., & Preskill, J. (1996) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 268

Module-Lattice-Based Key-Encapsulation Mechanism Standard

National Institute of Standards and Technology (US) (2024)

Cryptography and Data SecurityCryptography and Residue Arithmetic

Cited by 268

AddGraph: Anomaly Detection in Dynamic Graph Using Attention-based Temporal GCN

Zheng, L., Li, Z., Li, J., Li, Z., & Gao, J. (2019) · Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence

Advanced Graph Neural NetworksAnomaly Detection Techniques and Applications

Cited by 268

Designing fair AI for managing employees in organizations: a review, critique, and design agenda

Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020) · Human–Computer Interaction

Ethics and Social Impacts of AIAI and HR Technologies

Cited by 268

Recommendations for Reporting Machine Learning Analyses in Clinical Research

Stevens, L. M., Mortazavi, B. J., Deo, R. C., Curtis, L., & Kao, D. P. (2020) · Circulation: Cardiovascular Quality and Outcomes

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 268

Long-term cancer survival prediction using multimodal deep learning

Vale-Silva, L. A., & Rohr, K. (2021) · Scientific Reports

Machine Learning in HealthcareRadiomics and Machine Learning in Medical Imaging

Cited by 268

The relevance of software documentation, tools and technologies: a survey

Forward, A., & Lethbridge, T. C. (2002) · Proceedings of the 2002 ACM symposium on Document engineering

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 268

Ethics-Based Auditing to Develop Trustworthy AI

Mökander, J., & Floridi, L. (2021) · Minds and Machines

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 268

One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques

Arya, V., Bellamy, R. K. E., Chen, P.-Y., Dhurandhar, A., Hind, M., Hoffman, S. C., Houde, S., Liao, Q. V., Luss, R., Mojsilović, A., et al. (2019) · arXiv

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

Cited by 268

REMIND Your Neural Network to Prevent Catastrophic Forgetting

Hayes, T. L., Kafle, K., Shrestha, R., Acharya, M., & Kanan, C. (2019) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 268