Jonathan Weber

Active 1986–2026

174
Papers
18,608
Citations
78
h-index
119
i10-index

Citations

Citations per year for Jonathan Weber1954: 1 citations1987: 16 citations1988: 31 citations1989: 28 citations1990: 40 citations1991: 42 citations1992: 30 citations1993: 30 citations1994: 19 citations1995: 22 citations1996: 60 citations1997: 89 citations1998: 112 citations1999: 86 citations2000: 91 citations2001: 71 citations2002: 87 citations2003: 84 citations2004: 119 citations2005: 76 citations2006: 83 citations2007: 75 citations2008: 84 citations2009: 107 citations2010: 106 citations2011: 102 citations2012: 99 citations2013: 77 citations2014: 63 citations2015: 66 citations2016: 60 citations2017: 59 citations2018: 52 citations2019: 333 citations2020: 576 citations2021: 695 citations2022: 793 citations2023: 808 citations2024: 952 citations2025: 837 citations2026: 199 citations2027: 2 citations1955–1986: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 1,759 citing papers, 19.4% of this breakdownChina: 1,115 citing papers, 12.3% of this breakdownUnited Kingdom: 767 citing papers, 8.4% of this breakdownFrance: 475 citing papers, 5.2% of this breakdownGermany: 472 citing papers, 5.2% of this breakdownAustralia: 322 citing papers, 3.5% of this breakdownCanada: 308 citing papers, 3.4% of this breakdownJapan: 277 citing papers, 3% of this breakdownItaly: 257 citing papers, 2.8% of this breakdownSpain: 253 citing papers, 2.8% of this breakdownIndia: 227 citing papers, 2.5% of this breakdownSwitzerland: 196 citing papers, 2.2% of this breakdown
0%19.4%Other 29.3%

Fields

  • Computer Science36%
  • Immunology and Microbiology22.2%
  • Medicine17.5%
  • Engineering9.1%
  • Biochemistry, Genetics and Molecular Biology2.6%
  • Environmental Science2.3%
  • Other10.3%

Topics

  • Time Series Analysis and Forecasting7.9%
  • HIV Research and Treatment6.5%
  • Anomaly Detection Techniques and Applications6%
  • HIV/AIDS drug development and treatment3.4%
  • HIV/AIDS Research and Interventions2.9%
  • Immune Cell Function and Interaction2.5%
  • Other70.8%

Coauthors

All papers

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  1. Deep learning for time series classification: a review

    Authors: , , , , - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2019 cited by 3,202

  2. InceptionTime: Finding AlexNet for Time Series Classification

    Authors: , , , , , , , , , - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2020 cited by 1,446

  3. Deep learning for colon cancer histopathological images analysis

    Authors: , , , , , , , - Computers in Biology and Medicine, Comput. Biol. Medicine 2021 cited by 235

  4. Transfer learning for time series classification

    Authors: , , , , - IEEE International Conference on Big Data (Big Data), IEEE BigData 2018 cited by 270

  5. End-to-end deep representation learning for time series clustering: a comparative study

    Authors: , , , - Data Mining and Knowledge Discovery, Data Min. Knowl. Discov. 2021 cited by 80

  6. Deep Learning For Time Series Classification Using New Hand-Crafted Convolution Filters

    Authors: , , , - IEEE International Conference on Big Data (Big Data), IEEE Big Data 2022 cited by 44

  7. An Approach to Multiple Comparison Benchmark Evaluations that is Stable Under Manipulation of the Comparate Set

    Authors: , , , , , , , , , , - arXiv (Cornell University), CoRR 2023 cited by 30

  8. Adversarial Attacks on Deep Neural Networks for Time Series Classification

    Authors: , , , , - International Joint Conference on Neural Networks (IJCNN) 2019 cited by 138

  9. Accurate and interpretable evaluation of surgical skills from kinematic data using fully convolutional neural networks

    Authors: , , , , - International Journal of Computer Assisted Radiology and Surgery, Int. J. Comput. Assist. Radiol. Surg. 2019 cited by 105

  10. LITE: Light Inception with boosTing tEchniques for Time Series Classification

    Authors: , , , , - IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA) 2023 cited by 29

  11. Recent trends in crowd analysis: A review

    Authors: , , , , - Machine Learning with Applications 2021 cited by 79

  12. Understanding fibrosis pathogenesis via modeling macrophage-fibroblast interplay in immune-metabolic context

    Authors: , , , , , , , , , , , - Nature Communications 2022 cited by 66

  13. Deep Neural Network Ensembles for Time Series Classification

    Authors: , , , , - International Joint Conference on Neural Networks (IJCNN) 2019 cited by 94

  14. Data augmentation using synthetic data for time series classification with deep residual networks

    Authors: , , , , - arXiv (Cornell University), CoRR 2018 cited by 82

  15. Spread of HTLV-I Between Lymphocytes by Virus-Induced Polarization of the Cytoskeleton

    Authors: , , , , , , , , - Science 2003 cited by 730

  16. Aging and the evolution of comorbidities among HIV-positive individuals in a European cohort

    Authors: , , , , , , , , , , , , , , , , , , , , , - AIDS 2018 cited by 131

  17. HIV-1 DNA predicts disease progression and post-treatment virological control

    Authors: , , , , , , , , , , , , , , , , , , - eLife 2014 cited by 307

  18. Evaluating Surgical Skills from Kinematic Data Using Convolutional Neural Networks

    Authors: , , , , - Lecture notes in computer science, MICCAI (4) 2018 cited by 121

  19. Invasive versus non-invasive management of older patients with non-ST elevation myocardial infarction (SENIOR-NSTEMI): a cohort study based on routine clinical data

    Authors: , , , , , , , , , , , , , , , , , , , , , , , , , , , - The Lancet 2020 cited by 114

  20. Trends in Cardiovascular MRI and CT in the U.S. Medicare Population from 2012 to 2017

    Authors: , - Radiology Cardiothoracic Imaging 2021 cited by 50

  21. Diagnostic Performance and Clinical Impact of Photon-Counting Detector Computed Tomography in Coronary Artery Disease

    Authors: , , , , , , , , , , , , , , , , , , - Journal of the American College of Cardiology 2024 cited by 74

  22. Surgical motion analysis using discriminative interpretable patterns

    Authors: , , , , , , , , , - Artificial Intelligence in Medicine, Artif. Intell. Medicine 2018 cited by 63

  23. Neural Architecture Search for Time Series Classification

    Authors: , , , , , , , - International Joint Conference on Neural Networks (IJCNN) 2020 cited by 25

  24. Data Augmentation for Time Series Classification with Deep Learning Models

    Authors: , , , , - Lecture notes in computer science, AALTD@ECML/PKDD 2022 cited by 17