Check computer science papers: citations, claims and retractions

A Quick Review of Machine Learning Algorithms

Ray, S. (2019) · 2019 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing (COMITCon)

Data Mining and Machine Learning ApplicationsMachine Learning and Algorithms

Cited by 1,070

Observed versus latent features for knowledge base and text inference

Toutanova, K., & Chen, D. (2015) · Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality

Advanced Graph Neural NetworksTopic Modeling

Cited by 1,070

The "Wake-Sleep" Algorithm for Unsupervised Neural Networks

Hinton, G. E., Dayan, P., Frey, B. J., & Neal, R. M. (1995) · Science

Neural Networks and ApplicationsNeural dynamics and brain function

Cited by 1,070

Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis

Litjens, G., Sánchez, C. I., Timofeeva, N., Hermsen, M., Nagtegaal, I., Kovacs, I., Hulsbergen - van de Kaa, C., Bult, P., van Ginneken, B., & van der Laak, J. (2016) · Scientific Reports

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 1,069

Two-bit gates are universal for quantum computation

DiVincenzo, D. P. (1995) · Physical Review A

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 1,069

My body in the brain: A neurocognitive model of body-ownership.

Tsakiris, M. (2010) · Neuropsychologia

Virtual Reality Applications and ImpactsMultisensory perception and integration

Cited by 1,069

RULER: What's the Real Context Size of Your Long-Context Language Models?

Hsieh, C.-P., Sun, S., Kriman, S., Acharya, S., Rekesh, D., Jia, F., Zhang, Y., & Ginsburg, B. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1,068

Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions

Andoni, A., & Indyk, P. (2006) · 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06)

Advanced Image and Video Retrieval TechniquesAlgorithms and Data Compression

Cited by 1,067

Density-Aware Single Image De-raining Using a Multi-stream Dense Network

Zhang, H., & Patel, V. M. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition

Image Enhancement TechniquesImage and Signal Denoising Methods

Cited by 1,066

Efficient region tracking with parametric models of geometry and illumination

Hager, G. D., & Belhumeur, P. N. (1998) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Video Surveillance and Tracking MethodsAdvanced Vision and Imaging

Cited by 1,066

Finding your Way in the Fog: Towards a Comprehensive Definition of Fog Computing

Vaquero, L. M., & Rodero-Merino, L. (2014) · ACM SIGCOMM Computer Communication Review

IoT and Edge/Fog ComputingSoftware-Defined Networks and 5G

Cited by 1,066

Word embeddings quantify 100 years of gender and ethnic stereotypes

Garg, N., Schiebinger, L., Jurafsky, D., & Zou, J. (2018) · Proceedings of the National Academy of Sciences

Ethics and Social Impacts of AIComputational and Text Analysis Methods

Cited by 1,065

Dota 2 with Large Scale Deep Reinforcement Learning

OpenAI, :, Berner, C., Brockman, G., Chan, B., Cheung, V., Dębiak, P., Dennison, C., Farhi, D., Fischer, Q., et al. (2019) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 1,065

Clustering trees: a visualization for evaluating clusterings at multiple resolutions

Zappia, L., & Oshlack, A. (2018) · GigaScience

Advanced Clustering Algorithms ResearchData Visualization and Analytics

Cited by 1,064

Generating Long Sequences with Sparse Transformers

Child, R., Gray, S., Radford, A., & Sutskever, I. (2019) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1,063

The effects of a visual fidelity criterion of the encoding of images

Mannos, J., & Sakrison, D. (1974) · IEEE Transactions on Information Theory

Advanced Data Compression TechniquesImage and Video Quality Assessment

Cited by 1,063

Cache in the air: exploiting content caching and delivery techniques for 5G systems

Wang, X., Chen, M., Taleb, T., Ksentini, A., & Leung, V. (2014) · IEEE Communications Magazine

Caching and Content DeliveryIoT and Edge/Fog Computing

Cited by 1,063

Interpreting the Latent Space of GANs for Semantic Face Editing

Shen, Y., Gu, J., Tang, X., & Zhou, B. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisFace recognition and analysis

Cited by 1,063

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

Liang, T., He, Z., Jiao, W., Wang, X., Wang, Y., Wang, R., Yang, Y., Shi, S., & Tu, Z. (2024) · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 1,062

Sentiment strength detection for the social web

Thelwall, M., Buckley, K., & Paltoglou, G. (2012) · Journal of the American Society for Information Science and Technology

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 1,062

Traffic-Sign Detection and Classification in the Wild

Zhu, Z., Liang, D., Zhang, S., Huang, X., Li, B., & Hu, S. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 1,062

CityPersons: A Diverse Dataset for Pedestrian Detection

Zhang, S., Benenson, R., & Schiele, B. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 1,061

BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Gu, T., Dolan-Gavitt, B., & Garg, S. (2017) · arXiv

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 1,061

Imitation Learning: A Survey of Learning Methods

Hussein, A., Gaber, M. M., Elyan, E., & Jayne, C. (2018) · ACM Computing Surveys

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 1,060