Check computer science papers: citations, claims and retractions

Conditional Neural Processes

Garnelo, M., Rosenbaum, D., Maddison, C. J., Ramalho, T., Saxton, D., Shanahan, M., Teh, Y. W., Rezende, D. J., & Eslami, S. M. A. (2018) · arXiv

Gaussian Processes and Bayesian InferenceNeural Networks and Applications

Cited by 287

A machine learning model to predict the risk of 30-day readmissions in patients with heart failure: a retrospective analysis of electronic medical records data

Golas, S. B., Shibahara, T., Agboola, S., Otaki, H., Sato, J., Nakae, T., Hisamitsu, T., Kojima, G., Felsted, J., Kakarmath, S., et al. (2018) · BMC Medical Informatics and Decision Making

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 287

Does learning require memorization? a short tale about a long tail

Feldman, V. (2020) · Proceedings of the 52nd Annual ACM SIGACT Symposium on Theory of Computing

Privacy-Preserving Technologies in DataStochastic Gradient Optimization Techniques

Cited by 287

VideoEdge: Processing Camera Streams using Hierarchical Clusters

Hung, C.-C., Ananthanarayanan, G., Bodik, P., Golubchik, L., Yu, M., Bahl, P., & Philipose, M. (2018) · 2018 IEEE/ACM Symposium on Edge Computing (SEC)

IoT and Edge/Fog ComputingAdvanced Database Systems and Queries

Cited by 287

Weakly Supervised Cascaded Convolutional Networks

Diba, A., Sharma, V., Pazandeh, A., Pirsiavash, H., & Van Gool, L. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 287

Hardware-oriented Approximation of Convolutional Neural Networks

Gysel, P., Motamedi, M., & Ghiasi, S. (2016) · arXiv

Advanced Neural Network ApplicationsNumerical Methods and Algorithms

Cited by 287

PERSISTENCE BARCODES FOR SHAPES

CARLSSON, G., ZOMORODIAN, A., COLLINS, A., & GUIBAS, L. J. (2005) · International Journal of Shape Modeling

Topological and Geometric Data AnalysisGeometric and Algebraic Topology

Cited by 287

Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM

Wang, H., Wang, J., & Agapito, L. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Robotics and Sensor-Based Localization3D Shape Modeling and Analysis

Cited by 287

Emotion Recognition from Multiband EEG Signals Using CapsNet

Chao, H., Dong, L., Liu, Y., & Lu, B. (2019) · Sensors

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 287

Learning deep physiological models of affect

Martinez, H. P., Bengio, Y., & Yannakakis, G. N. (2013) · IEEE Computational Intelligence Magazine

Emotion and Mood RecognitionContext-Aware Activity Recognition Systems

Cited by 287

Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language

Denny, P., Kumar, V., & Giacaman, N. (2023) · Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1

Teaching and Learning ProgrammingSoftware Engineering Research

Cited by 287

Effectiveness analysis of machine learning classification models for predicting personalized context-aware smartphone usage

Sarker, I. H., Kayes, A. S. M., & Watters, P. (2019) · Journal of Big Data

Context-Aware Activity Recognition SystemsData Mining and Machine Learning Applications

Cited by 287

Gender differences and bias in open source: pull request acceptance of women versus men

Terrell, J., Kofink, A., Middleton, J., Rainear, C., Murphy-Hill, E., Parnin, C., & Stallings, J. (2017) · PeerJ Computer Science

Open Source Software InnovationsGender and Technology in Education

Cited by 287

Towards an elastic distributed SDN controller

Dixit, A., Hao, F., Mukherjee, S., Lakshman, T. V., & Kompella, R. (2013) · ACM SIGCOMM Computer Communication Review

Software-Defined Networks and 5GAdvanced Optical Network Technologies

Cited by 287

Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection

Ravfogel, S., Elazar, Y., Gonen, H., Twiton, M., & Goldberg, Y. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 287

Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Ho, X., Duong Nguyen, A.-K., Sugawara, S., & Aizawa, A. (2020) · Proceedings of the 28th International Conference on Computational Linguistics

Topic ModelingMultimodal Machine Learning Applications

Cited by 287

Qubit Coupled Cluster Method: A Systematic Approach to Quantum Chemistry on a Quantum Computer

Ryabinkin, I. G., Yen, T.-C., Genin, S. N., & Izmaylov, A. F. (2018) · Journal of Chemical Theory and Computation

Quantum Computing Algorithms and ArchitectureAdvanced Chemical Physics Studies

Cited by 287

” How old do you think I am?” A study of language and age in Twitter

Nguyen, D., Gravel, R., Trieschnigg, D., & Meder, T. (2021) · Proceedings of the International AAAI Conference on Web and Social Media

Authorship Attribution and ProfilingMental Health via Writing

Cited by 287

Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model

Smith, S., Patwary, M., Norick, B., LeGresley, P., Rajbhandari, S., Casper, J., Liu, Z., Prabhumoye, S., Zerveas, G., Korthikanti, V., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 286

AI-assisted peer review

Checco, A., Bracciale, L., Loreti, P., Pinfield, S., & Bianchi, G. (2021) · Humanities and Social Sciences Communications

Ethics and Social Impacts of AIPublishing and Scholarly Communication

Cited by 286

Securing the Internet of Things in the Age of Machine Learning and Software-Defined Networking

Restuccia, F., D'Oro, S., & Melodia, T. (2018) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingNetwork Security and Intrusion Detection

Cited by 286

$\mathsf{LightChain}$: A Lightweight Blockchain System for Industrial Internet of Things

Liu, Y., Wang, K., Lin, Y., & Xu, W. (2019) · IEEE Transactions on Industrial Informatics

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 286

A Latent Variable Model Approach to PMI-based Word Embeddings

Arora, S., Li, Y., Liang, Y., Ma, T., & Risteski, A. (2016) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 286

xLSTM: Extended Long Short-Term Memory

Beck, M., Pöppel, K., Spanring, M., Auer, A., Prudnikova, O., Kopp, M., Klambauer, G., Brandstetter, J., & Hochreiter, S. (2024) · Advances in Neural Information Processing Systems 37

Neural Networks and ApplicationsTopic Modeling

Cited by 286