Bernhard Schölkopf

144.9k total citations · 29 hit papers
583 papers, 79.6k citations indexed

About

Bernhard Schölkopf is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Bernhard Schölkopf has authored 583 papers receiving a total of 79.6k indexed citations (citations by other indexed papers that have themselves been cited), including 294 papers in Artificial Intelligence, 154 papers in Computer Vision and Pattern Recognition and 77 papers in Cognitive Neuroscience. Recurrent topics in Bernhard Schölkopf's work include Neural Networks and Applications (90 papers), Face and Expression Recognition (72 papers) and Bayesian Modeling and Causal Inference (53 papers). Bernhard Schölkopf is often cited by papers focused on Neural Networks and Applications (90 papers), Face and Expression Recognition (72 papers) and Bayesian Modeling and Causal Inference (53 papers). Bernhard Schölkopf collaborates with scholars based in Germany, United States and United Kingdom. Bernhard Schölkopf's co-authors include Alex Smola, Alexander J. Smola, Klaus‐Robert Müller, John Platt, Gunnar Rätsch, Robert C. Williamson, Christopher J. C. Burges, Jason Weston, Mika Sirén and John Shawe‐Taylor and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Bernhard Schölkopf

569 papers receiving 75.6k citations

Hit Papers

A tutorial on support vector regression 1997 2026 2006 2016 2004 2001 1998 1998 1999 2.5k 5.0k 7.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A tutorial on support vector regression
    2004 9.2k citations Alex Smola, Bernhard Schölkopf profile →
  2. Learning with Kernels
    2001 6.2k citations Bernhard Schölkopf et al. profile →
  3. Nonlinear Component Analysis as a Kernel Eigenvalue Problem
    1998 5.3k citations Bernhard Schölkopf et al. profile →
  4. Support vector machines
    1998 4.4k citations John Platt, Bernhard Schölkopf et al. profile →
  5. Advances in kernel methods: support vector learning
    1999 4.1k citations Bernhard Schölkopf et al. profile →
  6. Estimating the Support of a High-Dimensional Distribution
    2001 3.8k citations Bernhard Schölkopf, John Platt et al. profile →
  7. Learning with Local and Global Consistency
    2003 2.5k citations Bernhard Schölkopf et al. MPG.PuRe (Max Planck Society) profile →
  8. An introduction to kernel-based learning algorithms
    2001 2.5k citations Gunnar Rätsch, Bernhard Schölkopf et al. profile →
  9. A gene expression map of Arabidopsis thaliana development
    2005 2.0k citations Bernhard Schölkopf, Detlef Weigel et al. profile →
  10. New Support Vector Algorithms
    2000 2.0k citations Bernhard Schölkopf, Alex Smola et al. profile →
  11. Fisher discriminant analysis with kernels
    2003 1.8k citations Gunnar Rätsch, Bernhard Schölkopf et al. profile →
  12. Learning with Kernels
    2001 1.8k citations Bernhard Schölkopf MPG.PuRe (Max Planck Society) profile →
  13. Support Vector Method for Novelty Detection
    1999 1.4k citations Bernhard Schölkopf, Alex Smola et al. UCL Discovery (University College London) profile →
  14. Integrating structured biological data by Kernel Maximum Mean Discrepancy
    2006 1.1k citations Arthur Gretton, Bernhard Schölkopf et al. Bioinformatics profile →
  15. A kernel two-sample test
    2012 1.0k citations Arthur Gretton, Bernhard Schölkopf et al. profile →
  16. Comparing support vector machines with Gaussian kernels to radial basis function classifiers
    1997 1.0k citations Bernhard Schölkopf et al. profile →
  17. Large Scale Multiple Kernel Learning
    2006 853 citations Gunnar Rätsch, Bernhard Schölkopf et al. profile →
  18. Input space versus feature space in kernel-based methods
    1999 823 citations Bernhard Schölkopf, Gunnar Rätsch et al. profile →
  19. Semi-Supervised Learning (Chapelle, O. et al., Eds.; 2006) [Book reviews]
    2009 648 citations Olivier Chapelle, Bernhard Schölkopf et al. profile →
  20. Towards Total Recall in Industrial Anomaly Detection
    2022 622 citations Bernhard Schölkopf et al. profile →
  21. Kernel PCA and De-Noising in Feature Spaces
    1998 535 citations Bernhard Schölkopf, Alex Smola et al. profile →
  22. Common Sequence Polymorphisms Shaping Genetic Diversity in Arabidopsis thaliana
    2007 526 citations Richard M. Clark, Gabriele Schweikert et al. Science profile →
  23. Toward Causal Representation Learning
    2021 519 citations Bernhard Schölkopf, Stefan Bauer et al. profile →
  24. Support Vector Machines and Kernels for Computational Biology
    2008 501 citations Bernhard Schölkopf, Gunnar Rätsch et al. PLoS Computational Biology profile →
  25. Ranking on Data Manifolds
    2003 469 citations Arthur Gretton, Bernhard Schölkopf et al. MPG.PuRe (Max Planck Society) profile →
  26. Learning to Deblur
    2015 376 citations Bernhard Schölkopf et al. profile →
  27. Elements of Causal Inference: Foundations and Learning Algorithms
    2017 358 citations Dominik Janzing, Bernhard Schölkopf et al. profile →
  28. Transfer Learning in Brain-Computer Interfaces Abstract\uFFFDThe performance of brain-computer interfaces (BCIs) improves with the amount of avail
    2016 314 citations Bernhard Schölkopf et al. profile →
  29. Wasserstein Auto-Encoders
    2018 262 citations Bernhard Schölkopf et al. MPG.PuRe (Max Planck Society) profile →

Peers

Bernhard Schölkopf
Comparison fields: 5 of 237
  • Artificial Intelligence 31.3k
  • Computer Vision and Pattern Recognition 23.7k
  • Molecular Biology 7.8k
  • Control and Systems Engineering 7.7k
  • Signal Processing 7.4k
Replace Michael I. Jordan with:
Michael I. Jordan United States
Ilya Sutskever Canada
Chih‐Jen Lin Taiwan
Jürgen Schmidhuber Switzerland
Corinna Cortes United States
Yann LeCun United States
Jerome H. Friedman United States
Andrew Y. Ng United States
Trevor Hastie United States
Alex Krizhevsky Canada
Michael I. Jordan United States View profile →
Citations per field, relative to Bernhard Schölkopf
Bernhard Schölkopf · 1×
Citations per year, relative to Bernhard Schölkopf
Bernhard Schölkopf · 1×

Countries citing papers authored by Bernhard Schölkopf

Since Specialization
Citations

This map shows the geographic impact of Bernhard Schölkopf's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bernhard Schölkopf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard Schölkopf more than expected).

Fields of papers citing papers by Bernhard Schölkopf

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bernhard Schölkopf. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bernhard Schölkopf. The network helps show where Bernhard Schölkopf may publish in the future.

Co-authorship network of co-authors of Bernhard Schölkopf

This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard Schölkopf. A scholar is included among the top collaborators of Bernhard Schölkopf based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bernhard Schölkopf. Bernhard Schölkopf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1
CausalCite: A Causal Formulation of Paper Citations
2024 ·(unknown), Zhijing Jin, (unknown), (unknown), (unknown), (unknown), Bernhard Schölkopf
0
2
Moûsai: Efficient Text-to-Music Diffusion Models
2024 ·(unknown), (unknown), Zhijing Jin, Bernhard Schölkopf
8
3
The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning
2024 ·Infoscience (Ecole Polytechnique Fédérale de Lausanne) ·(unknown), (unknown), Bernhard Schölkopf, Boi Faltings
1
4
A diverse Multilingual News Headlines Dataset from around the World
2024 ·(unknown), Bernhard Schölkopf
2
5
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good
2023 ·Repository for Publications and Research Data (ETH Zurich) ·(unknown), (unknown), Bernhard Schölkopf, Tom Hope, Mrinmaya Sachan, Rada Mihalcea
1
6
Parameterizing pressure–temperature profiles of exoplanet atmospheres with neural networks
2023 ·Astronomy and Astrophysics ·(unknown), Daniel Angerhausen, (unknown), Eleonora Alei, Sascha P. Quanz, Bernhard Schölkopf
5
7
Multiplane Diffractive Acoustic Networks
2023 ·IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control ·Athanasios G. Athanassiadis, (unknown), Kai Melde, (unknown), Bernhard Schölkopf, Peer Fischer
6
8
Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases
2023 ·PLoS Computational Biology ·Arash Mehrjou, (unknown), (unknown), Samir Bhatt, Bernhard Schölkopf, Stefan Bauer
1
9
Regret Bounds for Gaussian-Process Optimization in Large Domains
2021 ·arXiv (Cornell University) ·(unknown), Bernhard Schölkopf, Andreas Krause
1
10
Kernel Distributionally Robust Optimization: Generalized Duality Theorem and Stochastic Approximation
2021 ·International Conference on Artificial Intelligence and Statistics ·Jia-Jie Zhu, Wittawat Jitkrittum, Moritz Diehl, Bernhard Schölkopf
3
11
DeepMAsED: evaluating the quality of metagenomic assemblies
2020 ·Bioinformatics ·(unknown), Mateo Rojas-Carulla, Ruth E. Ley, Bernhard Schölkopf, Nicholas D. Youngblut
30
12
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach
2020 ·Cambridge University Engineering Department Publications Database ·Amir-Hossein Karimi, Julius von Kügelgen, Bernhard Schölkopf, Isabel Valera
7
13
Learning Independent Causal Mechanisms
2018 ·MPG.PuRe (Max Planck Society) ·Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schölkopf
27
14
Probabilistic Modeling of Human Dynamics for Intention Inference
2012 ·Spiral (Imperial College London) ·(unknown), (unknown), (unknown), David Vogt, Bernhard Schölkopf, Jan Peters
4
15
On Causal Discovery with Cyclic Additive Noise Models
2011 ·MPG.PuRe (Max Planck Society) ·Joris M. Mooij, Dominik Janzing, Tom Heskes, Bernhard Schölkopf
33
16
Common Sequence Polymorphisms Shaping Genetic Diversity in Arabidopsis thaliana breakdown →
2007 ·Science ·Richard M. Clark, Gabriele Schweikert, Christopher Toomajian, Stephan Ossowski, Georg Zeller, Paul Shinn, Norman Warthmann, Tina T. Hu, Glenn K. Fu, David A. Hinds, Huaming Chen, Kelly A. Frazer, Daniel H. Huson, Bernhard Schölkopf, Magnus Nordborg, Gunnar Rätsch, Joseph R. Ecker, Detlef Weigel
526
17
A Kernel Statistical Test of Independence
2007 ·ANU Open Research (Australian National University) ·Arthur Gretton, Kenji Fukumizu, Choon Hui Teo, Le Song, Bernhard Schölkopf, Alex Smola
317
18
Advances in Neural Information Processing Systems 18: Proceedings of the 2005 Conference
2006 ·Max Planck Institute for Plasma Physics ·(unknown), Bernhard Schölkopf, John Platt
6
19
Estimating the Leave-One-Out Error for Classification Learning with SVMs
2001 ·UCL Discovery (University College London) ·Arthur Gretton, Ralf Herbrich, Olivier Chapelle, Bernhard Schölkopf, (unknown)
3
20
Support Vector Novelty Detection Applied to Jet Engine Vibration Spectra
2000 ·Oxford University Research Archive (ORA) (University of Oxford) ·Paul Hayton, Bernhard Schölkopf, Lionel Tarassenko, (unknown)
69

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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