Check computer science papers: citations, claims and retractions

Towards a Better Metric for Evaluating Question Generation Systems

Nema, P., & Khapra, M. M. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Natural Language Processing TechniquesTopic Modeling

Cited by 106

Intelligent Detection of IoT Botnets Using Machine Learning and Deep Learning

Kim, J., Shim, M., Hong, S., Shin, Y., & Choi, E. (2020) · Applied Sciences

Network Security and Intrusion DetectionInternet of Things and AI

Cited by 106

Replay in Deep Learning: Current Approaches and Missing Biological Elements

Hayes, T. L., Krishnan, G. P., Bazhenov, M., Siegelmann, H. T., Sejnowski, T. J., & Kanan, C. (2021) · Neural Computation

Domain Adaptation and Few-Shot LearningMemory and Neural Mechanisms

Cited by 106

AvgNet: Adaptive Visibility Graph Neural Network and Its Application in Modulation Classification

Xuan, Q., Zhou, J., Qiu, K., Chen, Z., Xu, D., Zheng, S., & Yang, X. (2022) · IEEE Transactions on Network Science and Engineering

Wireless Signal Modulation ClassificationAdvanced Graph Neural Networks

Cited by 106

Quantum Machine Learning: A tutorial

Martín-Guerrero, J. D., & Lamata, L. (2022) · Neurocomputing

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 106

Public Subsidies for Open Source? Some Economic Policy Issues of the Software Market

Schmidt, K. M., & Schnitzer, M. (2002) · SSRN Electronic Journal

Open Source Software InnovationsDigital Platforms and Economics

Cited by 106

Deep Learning in Medical Image Registration

Chen, X., Diaz-Pinto, A., Ravikumar, N., & Frangi, A. (2020) · Progress in Biomedical Engineering

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 106

Quantum algorithm for simulating the dynamics of an open quantum system

Wang, H., Ashhab, S., & Nori, F. (2011) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 106

IBM Federated Learning: an Enterprise Framework White Paper V0.1

Ludwig, H., Baracaldo, N., Thomas, G., Zhou, Y., Anwar, A., Rajamoni, S., Ong, Y., Radhakrishnan, J., Verma, A., Sinn, M., et al. (2020) · arXiv

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 106

Dense Associative Memory Is Robust to Adversarial Inputs

Krotov, D., & Hopfield, J. (2018) · Neural Computation

Adversarial Robustness in Machine LearningNeural Networks and Applications

Cited by 106

Dual Conditional Cross-Entropy Filtering of Noisy Parallel Corpora

Junczys-Dowmunt, M. (2018) · Proceedings of the Third Conference on Machine Translation: Shared Task Papers

Natural Language Processing TechniquesTopic Modeling

Cited by 106

CPU workload forecasting of machines in data centers using LSTM recurrent neural networks and ARIMA models

Janardhanan, D., & Barrett, E. (2017) · 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST)

Cloud Computing and Resource ManagementEnergy Efficiency in Computing

Cited by 106

Power analysis attacks on the AES-128 S-box using differential power analysis (DPA) and correlation power analysis (CPA)

Lo, O., Buchanan, W. J., & Carson, D. (2017) · Journal of Cyber Security Technology

Cryptographic Implementations and SecurityCoding theory and cryptography

Cited by 106

Explainable artificial intelligence (XAI) in radiology and nuclear medicine: a literature review

de Vries, B. M., Zwezerijnen, G. J. C., Burchell, G. L., van Velden, F. H. P., Menke-van der Houven van Oordt, C. W., & Boellaard, R. (2023) · Frontiers in Medicine

Explainable Artificial Intelligence (XAI)Artificial Intelligence in Healthcare and Education

Cited by 106

Smart Contract Based Data Trading Mode Using Blockchain and Machine Learning

Xiong, W., & Xiong, L. (2019) · IEEE Access

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 106

Manifestations of task-induced stress in the acoustic speech signal.

Hecker, M. H. L., Stevens, K. N., von Bismarck, G., & Williams, C. E. (1968) · The Journal of the Acoustical Society of America

Emotion and Mood RecognitionPhonetics and Phonology Research

Cited by 106

Brain-Based Devices for the Study of Nervous Systems and the Development of Intelligent Machines

Krichmar, J. L., & Edelman, G. M. (2005) · Artificial Life

Psychiatry, Mental Health, NeuroscienceEmbodied and Extended Cognition

Cited by 106

Use, disuse, and misuse of automated refactorings

Vakilian, M., Chen, N., Negara, S., Rajkumar, B. A., Bailey, B. P., & Johnson, R. E. (2012) · 2012 34th International Conference on Software Engineering (ICSE)

Software Engineering ResearchSoftware Engineering Techniques and Practices

Cited by 106

Privacy in Deep Learning: A Survey

Mireshghallah, F., Taram, M., Vepakomma, P., Singh, A., Raskar, R., & Esmaeilzadeh, H. (2020) · arXiv

Privacy-Preserving Technologies in DataAdversarial Robustness in Machine Learning

Cited by 106

Quantum computational advantage via high-dimensional Gaussian boson sampling

Deshpande, A., Mehta, A., Vincent, T., Quesada, N., Hinsche, M., Ioannou, M., Madsen, L., Lavoie, J., Qi, H., Eisert, J., et al. (2022) · Science Advances

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 106

Federated Self-Supervised Learning of Multisensor Representations for Embedded Intelligence

Saeed, A., Salim, F. D., Ozcelebi, T., & Lukkien, J. (2021) · IEEE Internet of Things Journal

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 106

IoT reliability: a review leading to 5 key research directions

Moore, S. J., Nugent, C. D., Zhang, S., & Cleland, I. (2020) · CCF Transactions on Pervasive Computing and Interaction

IoT and Edge/Fog ComputingReliability and Maintenance Optimization

Cited by 106

A Validation of DRAM RAPL Power Measurements

Desrochers, S., Paradis, C., & Weaver, V. M. (2016) · Proceedings of the Second International Symposium on Memory Systems

Parallel Computing and Optimization TechniquesEnergy Efficiency in Computing

Cited by 106

Are explanations always important?: a study of deployed, low-cost intelligent interactive systems

Bunt, A., Lount, M., & Lauzon, C. (2012) · Proceedings of the 2012 ACM international conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Usability and User Interface Design

Cited by 106