Bernhard Schoelkopf

1.5k total citations
19 papers, 483 citations indexed

About

Bernhard Schoelkopf is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Signal Processing. According to data from OpenAlex, Bernhard Schoelkopf has authored 19 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 4 papers in Cognitive Neuroscience and 3 papers in Signal Processing. Recurrent topics in Bernhard Schoelkopf's work include Bayesian Modeling and Causal Inference (3 papers), Blind Source Separation Techniques (3 papers) and Natural Language Processing Techniques (3 papers). Bernhard Schoelkopf is often cited by papers focused on Bayesian Modeling and Causal Inference (3 papers), Blind Source Separation Techniques (3 papers) and Natural Language Processing Techniques (3 papers). Bernhard Schoelkopf collaborates with scholars based in Germany, United States and Switzerland. Bernhard Schoelkopf's co-authors include Mingming Gong, Kun Zhang, Sebastian Halder, Alireza Gharabaghi, Michael Bensch, Femke Nijboer, Suzanne Martens, Niels Birbaumer, J. Hill and Mrinmaya Sachan and has published in prestigious journals such as Clinical Neurophysiology, Frontiers in Human Neuroscience and ANU Open Research (Australian National University).

In The Last Decade

Bernhard Schoelkopf

19 papers receiving 467 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Bernhard Schoelkopf	237	147	90	84	35	19	483
John Choi	141 0.6×	86 0.6×	75 0.8×	34 0.4×	32 0.9×	15	356
Tsung-Yu Hsieh	174 0.7×	122 0.8×	31 0.3×	47 0.6×	44 1.3×	25	400
Jun-ichiro Hirayama	105 0.4×	137 0.9×	48 0.5×	23 0.3×	47 1.3×	24	318
Morteza Alamgir	80 0.3×	342 2.3×	35 0.4×	122 1.5×	90 2.6×	10	481
Mulugeta Semework	131 0.6×	123 0.8×	72 0.8×	60 0.7×	25 0.7×	14	391
Rasmus Elsborg Madsen	167 0.7×	153 1.0×	48 0.5×	47 0.6×	71 2.0×	16	394
C. Gielen	145 0.6×	130 0.9×	63 0.7×	32 0.4×	33 0.9×	16	388
Luca Didaci	304 1.3×	203 1.4×	124 1.4×	62 0.7×	217 6.2×	22	670
Yuanyuan Shen	114 0.5×	212 1.4×	87 1.0×	12 0.1×	41 1.2×	10	432

Countries citing papers authored by Bernhard Schoelkopf

Since Specialization

Citations

This map shows the geographic impact of Bernhard Schoelkopf'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 Schoelkopf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard Schoelkopf more than expected).

Fields of papers citing papers by Bernhard Schoelkopf

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bernhard Schoelkopf. 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 Schoelkopf. The network helps show where Bernhard Schoelkopf may publish in the future.

Co-authorship network of co-authors of Bernhard Schoelkopf

This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard Schoelkopf. A scholar is included among the top collaborators of Bernhard Schoelkopf 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 Schoelkopf. Bernhard Schoelkopf is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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19 of 19 papers shown

Mireshghallah, Fatemehsadat, et al.. (2023). Membership Inference Attacks against Language Models via Neighbourhood Comparison. 11330–11343. 27 indexed citations

Karimi, Amir-Hossein, et al.. (2023). Robustness Implies Fairness in Causal Algorithmic Recourse. 984–1001. 2 indexed citations

Shridhar, Kumar, et al.. (2023). A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models. 545–561. 9 indexed citations

Jin, Zhijing, et al.. (2022). Differentially Private Language Models for Secure Data Sharing. 4860–4873. 11 indexed citations

Shen, Xiaoyu, et al.. (2022). Logical Fallacy Detection. 7180–7198. 21 indexed citations

Jin, Zhijing, et al.. (2021). Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 9499–9513. 15 indexed citations

Jin, Zhijing, et al.. (2021). Mining the Cause of Political Decision-Making from Social Media: A Case Study of COVID-19 Policies across the US States. 288–301. 7 indexed citations

Gong, Mingming, Kun Zhang, Bernhard Schoelkopf, Dacheng Tao, & Philipp Geiger. (2015). Discovering Temporal Causal Relations from Subsampled Data. MPG.PuRe (Max Planck Society). 1898–1906. 23 indexed citations

Janzing, Dominik, et al.. (2015). Telling cause from effect in deterministic linear dynamical systems. arXiv (Cornell University). 285–294. 10 indexed citations

10.

Zhang, Kun, Mingming Gong, & Bernhard Schoelkopf. (2015). Multi-Source Domain Adaptation: A Causal View. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 81 indexed citations

11.

Muandet, Krikamol, Kenji Fukumizu, Bharath K. Sriperumbudur, Arthur Gretton, & Bernhard Schoelkopf. (2014). Kernel Mean Estimation and Stein Effect. MPG.PuRe (Max Planck Society). 10–18. 10 indexed citations

12.

Martens, Suzanne, Michael Bensch, Sebastian Halder, et al.. (2014). Epidural electrocorticography for monitoring of arousal in locked-in state. Frontiers in Human Neuroscience. 8. 861–861. 7 indexed citations

13.

López-Paz, David, Suvrit Sra, Alex Smola, Zoubin Ghahramani, & Bernhard Schoelkopf. (2014). Randomized Nonlinear Component Analysis. arXiv (Cornell University). 1359–1367. 56 indexed citations

14.

Daneshmand, Hadi, Manuel Gomez-Rodriguez, Le Song, & Bernhard Schoelkopf. (2014). Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm.. PubMed. 32(2). 793–801. 31 indexed citations

15.

Mülling, Katharina, et al.. (2013). Inverse Reinforcement Learning for Strategy Extraction. Max Planck Digital Library. 1–9. 2 indexed citations

16.

Kpotufe, Samory, Eleni Sgouritsa, Dominik Janzing, & Bernhard Schoelkopf. (2013). Consistency of Causal Inference under the Additive Noise Model. arXiv (Cornell University). 478–486. 11 indexed citations

17.

Hill, J., Michael Bensch, Suzanne Martens, et al.. (2010). Transition from the locked in to the completely locked-in state: A physiological analysis. Clinical Neurophysiology. 122(5). 925–933. 135 indexed citations

18.

Gretton, Arthur, Karsten Borgwardt, Malte J. Rasch, Bernhard Schoelkopf, & Alexander J. Smola. (2007). A kernel method to comparing distributions. ANU Open Research (Australian National University). 1 indexed citations

19.

Gretton, Arthur, Alexander J. Smola, Olivier Bousquet, et al.. (2005). Kernel Constrained Covariance for Dependence Measurement. Max Planck Institute for Plasma Physics. 112–119. 24 indexed citations

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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