Lehel Csató

1.5k total citations · 1 hit paper
34 papers, 836 citations indexed

About

Lehel Csató is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Lehel Csató has authored 34 papers receiving a total of 836 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 9 papers in Control and Systems Engineering and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Lehel Csató's work include Gaussian Processes and Bayesian Inference (11 papers), Control Systems and Identification (5 papers) and Machine Learning and Data Classification (4 papers). Lehel Csató is often cited by papers focused on Gaussian Processes and Bayesian Inference (11 papers), Control Systems and Identification (5 papers) and Machine Learning and Data Classification (4 papers). Lehel Csató collaborates with scholars based in Romania, United Kingdom and Germany. Lehel Csató's co-authors include Manfred Opper, Jan Peters, Dan Cornford, Bernhard Schölkopf, Ole Winther, Duy Nguyen-Tuong, D. J. Evans, Ernest Fokoué, Malte Kuß and Ben Ingram and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the Royal Statistical Society Series B (Statistical Methodology) and Neural Computation.

In The Last Decade

Lehel Csató

32 papers receiving 785 citations

Hit Papers

Sparse On-Line Gaussian Processes 2002 2026 2010 2018 2002 100 200 300 400
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. Sparse On-Line Gaussian Processes
    2002 478 citations Lehel Csató, Manfred Opper Neural Computation profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lehel Csató Romania 11 558 259 139 110 92 34 836
Edward Snelson United Kingdom 7 878 1.6× 337 1.3× 165 1.2× 258 2.3× 97 1.1× 10 1.3k
Hong Gu China 19 281 0.5× 128 0.5× 169 1.2× 78 0.7× 35 0.4× 72 1.0k
Eric Hartman United States 6 451 0.8× 224 0.9× 117 0.8× 34 0.3× 71 0.8× 11 740
Yuxin Zhao China 15 332 0.6× 699 2.7× 87 0.6× 72 0.7× 95 1.0× 90 1.2k
Zeyin Zhang China 14 252 0.5× 177 0.7× 104 0.7× 32 0.3× 56 0.6× 42 627
Gérard Bloch France 18 250 0.4× 452 1.7× 241 1.7× 49 0.4× 43 0.5× 64 1.2k
Soumalya Sarkar United States 17 216 0.4× 229 0.9× 52 0.4× 56 0.5× 97 1.1× 47 828
Dongpo Xu China 13 394 0.7× 114 0.4× 199 1.4× 41 0.4× 144 1.6× 60 814
Kumar S. Ray India 14 336 0.6× 185 0.7× 326 2.3× 93 0.8× 33 0.4× 73 778
Chan-Cheng Liu Taiwan 12 350 0.6× 117 0.5× 154 1.1× 157 1.4× 67 0.7× 33 648

Countries citing papers authored by Lehel Csató

Since Specialization
Citations

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

Fields of papers citing papers by Lehel Csató

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lehel Csató

This figure shows the co-authorship network connecting the top 25 collaborators of Lehel Csató. A scholar is included among the top collaborators of Lehel Csató 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 Lehel Csató. Lehel Csató 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
1.
Csató, Lehel, et al.. (2024). Wavelet-Based Prototype Learning for Medical Image Classification. 631–636.
2.
Csató, Lehel, et al.. (2023). Evaluating cooperative-competitive dynamics with deep Q-learning. Neurocomputing. 550. 126507–126507. 3 indexed citations
3.
Csató, Lehel, et al.. (2023). Wavelet-Based Prototype Networks. 277–282. 1 indexed citations
4.
Csató, Lehel, et al.. (2019). Medical Image Analysis with Semantic Segmentation and Active Learning. SHILAP Revista de lepidopterología. 64(1). 26–38. 2 indexed citations
5.
Csató, Lehel, et al.. (2017). The Use of Simple Cellular Automata in Image Processing. SHILAP Revista de lepidopterología. 62(2). 5–16. 3 indexed citations
6.
Indurkhya, Bipin, et al.. (2017). Finding patterns in visualizations of programs. 10. 1 indexed citations
7.
Csató, Lehel, et al.. (2014). Linear spectral hashing. Neurocomputing. 141. 117–123. 6 indexed citations
8.
Csató, Lehel, et al.. (2013). Linear spectral hashing.. The European Symposium on Artificial Neural Networks.
9.
Csató, Lehel, et al.. (2013). Alignment-based transfer learning for robot models. 1–7. 46 indexed citations
10.
Csató, Lehel, et al.. (2011). Active Learning with Clustering. 16. 127–139. 19 indexed citations
11.
Nguyen-Tuong, Duy, et al.. (2011). Learning inverse kinematics with structured prediction. 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems. 698–703. 36 indexed citations
12.
Ingram, Ben, et al.. (2010). Projected sequential Gaussian processes: A C++ tool for interpolation of large datasets with heterogeneous noise. Computers & Geosciences. 37(3). 295–309. 4 indexed citations
13.
Csató, Lehel, et al.. (2009). Bayesian Network Classifier for Medical Data Analysis. International Journal of Computers Communications & Control. 4(1). 65–65. 8 indexed citations
14.
Csató, Lehel, et al.. (2007). Kernel PCA based clustering for inducing features in text categorization.. The European Symposium on Artificial Neural Networks. 349–354. 3 indexed citations
15.
Ingram, Ben, Lehel Csató, & David Evans. (2005). Fast Spatial Interpolation using Sparse Gaussian Processes. 1(2). 2 indexed citations
16.
Cornford, Dan, Lehel Csató, & Manfred Opper. (2005). Sequential, Bayesian Geostatistics: A Principled Method for Large Data Sets. Geographical Analysis. 37(2). 183–199. 17 indexed citations
17.
Cornford, Dan, Lehel Csató, D. J. Evans, & Manfred Opper. (2004). Bayesian Analysis of the Scatterometer Wind Retrieval Inverse Problem: Some New Approaches. Journal of the Royal Statistical Society Series B (Statistical Methodology). 66(3). 609–626. 26 indexed citations
18.
Csató, Lehel, Manfred Opper, & Ole Winther. (2003). Tractable inference for probabilistic data models. Complexity. 8(4). 64–68. 5 indexed citations
19.
Csató, Lehel & Manfred Opper. (2002). Sparse On-Line Gaussian Processes. Neural Computation. 14(3). 641–668. 478 indexed citations breakdown →
20.
Csató, Lehel, et al.. (1999). Efficient Approaches to Gaussian Process Classification. Neural Information Processing Systems. 12. 251–257. 30 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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