Check computer science papers: citations, claims and retractions

DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning

Du, M., Li, F., Zheng, G., & Srikumar, V. (2017) · Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security

Software System Performance and ReliabilityAnomaly Detection Techniques and Applications

Cited by 1,835

Aleatoric and epistemic uncertainty in machine learning: an introduction to concepts and methods

Hüllermeier, E., & Waegeman, W. (2021) · Machine Learning

Adversarial Robustness in Machine LearningGaussian Processes and Bayesian Inference

Cited by 1,834

Language Models as Knowledge Bases?

Petroni, F., Rocktäschel, T., Riedel, S., Lewis, P., Bakhtin, A., Wu, Y., & Miller, A. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 1,834

From presence to consciousness through virtual reality.

Sanchez-Vives, M. V., & Slater, M. (2005) · Nature reviews. Neuroscience

Virtual Reality Applications and ImpactsPhilosophy and Theoretical Science

Cited by 1,831

Struck: Structured output tracking with kernels

Hare, S., Saffari, A., & Torr, P. H. S. (2011) · 2011 International Conference on Computer Vision

Video Surveillance and Tracking MethodsAdvanced Neural Network Applications

Cited by 1,831

Image Super-Resolution Via Iterative Refinement

Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., & Norouzi, M. (2022) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Image Processing TechniquesGenerative Adversarial Networks and Image Synthesis

Cited by 1,829

Image Super-Resolution via Iterative Refinement

Saharia, C., Ho, J., Chan, W., Salimans, T., Fleet, D. J., & Norouzi, M. (2021) · arXiv

Advanced Image Processing TechniquesGenerative Adversarial Networks and Image Synthesis

Cited by 1,829

SpanBERT: Improving Pre-training by Representing and Predicting Spans

Joshi, M., Chen, D., Liu, Y., Weld, D. S., Zettlemoyer, L., & Levy, O. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,827

Understanding deep image representations by inverting them

Mahendran, A., & Vedaldi, A. (2015) · 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 1,827

SpanBERT: Improving Pre-training by Representing and Predicting Spans

Joshi, M., Chen, D., Liu, Y., Weld, D. S., Zettlemoyer, L., & Levy, O. (2020) · Transactions of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 1,827

Predictors of Internet Use

Papacharissi, Z., & Rubin, A. M. (2000) · Journal of Broadcasting & Electronic Media

Media and Digital CommunicationTechnology Adoption and User Behaviour

Cited by 1,826

ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation

Paszke, A., Chaurasia, A., Kim, S., & Culurciello, E. (2016) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,826

Fuzzy logic

Zadeh, L. A. (1988) · Computer

Advanced Algebra and LogicFuzzy Logic and Control Systems

Cited by 1,824

Natural language processing: state of the art, current trends and challenges

Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023) · Multimedia Tools and Applications

Natural Language Processing TechniquesTopic Modeling

Cited by 1,823

Scientific discovery in the age of artificial intelligence.

Wang, H., Fu, T., Du, Y., Gao, W., Huang, K., Liu, Z., Chandak, P., Liu, S., Van Katwyk, P., Deac, A., et al. (2023) · Nature

Artificial Intelligence ApplicationsMachine Learning in Materials Science

Cited by 1,823

Satellite-to-ground quantum key distribution

Liao, S.-K., Cai, W.-Q., Liu, W.-Y., Zhang, L., Li, Y., Ren, J.-G., Yin, J., Shen, Q., Cao, Y., Li, Z.-P., et al. (2017) · Nature

Quantum Information and CryptographyWireless Communication Security Techniques

Cited by 1,821

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs

Monti, F., Boscaini, D., Masci, J., Rodola, E., Svoboda, J., & Bronstein, M. M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Graph Neural NetworksTopological and Geometric Data Analysis

Cited by 1,820

MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems

Chen, T., Li, M., Li, Y., Lin, M., Wang, N., Wang, M., Xiao, T., Xu, B., Zhang, C., & Zhang, Z. (2015) · arXiv

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 1,819

Efficient Memory Management for Large Language Model Serving with PagedAttention

Kwon, W., Li, Z., Zhuang, S., Sheng, Y., Zheng, L., Yu, C. H., Gonzalez, J., Zhang, H., & Stoica, I. (2023) · Proceedings of the 29th Symposium on Operating Systems Principles

Natural Language Processing TechniquesTopic Modeling

Cited by 1,817

The Balanced Accuracy and Its Posterior Distribution

Brodersen, K. H., Ong, C. S., Stephan, K. E., & Buhmann, J. M. (2010) · 2010 20th International Conference on Pattern Recognition

Imbalanced Data Classification TechniquesMachine Learning and Data Classification

Cited by 1,816

How to grow a mind: Statistics, structure, and abstraction

Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011) · Science

Bayesian Modeling and Causal InferenceCategorization, perception, and language

Cited by 1,815

Curiosity-Driven Exploration by Self-Supervised Prediction

Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 1,815

QLoRA: efficient finetuning of quantized LLMs

Dettmers, T., Pagnoni, A., Holtzman, A., & Zettlemoyer, L. (2023) · Advances in Neural Information Processing Systems 36

Topic ModelingAdvanced Neural Network Applications

Cited by 1,814

BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation

Yu, C., Gao, C., Wang, J., Yu, G., Shen, C., & Sang, N. (2021) · International Journal of Computer Vision

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,813