Malte Kuß

957 total citations
11 papers, 532 citations indexed

About

Malte Kuß is a scholar working on Artificial Intelligence, Analytical Chemistry and Statistics and Probability. According to data from OpenAlex, Malte Kuß has authored 11 papers receiving a total of 532 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 3 papers in Analytical Chemistry and 3 papers in Statistics and Probability. Recurrent topics in Malte Kuß's work include Gaussian Processes and Bayesian Inference (6 papers), Advanced Statistical Methods and Models (3 papers) and Spectroscopy and Chemometric Analyses (3 papers). Malte Kuß is often cited by papers focused on Gaussian Processes and Bayesian Inference (6 papers), Advanced Statistical Methods and Models (3 papers) and Spectroscopy and Chemometric Analyses (3 papers). Malte Kuß collaborates with scholars based in Germany. Malte Kuß's co-authors include Carl Edward Rasmussen, Felix A. Wichmann, Frank Jäkel, Lehel Csató, J Eichhorn, Nikos K. Logothetis, Bernhard Schölkopf, Alexander Zien, Andreas S. Tolias and Jason Weston and has published in prestigious journals such as Journal of Machine Learning Research, Journal of Vision and Journal of Visualization.

In The Last Decade

Malte Kuß

11 papers receiving 506 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Malte Kuß Germany	9	302	123	104	60	60	11	532
S.D. Katebi Iran	13	303 1.0×	161 1.3×	58 0.6×	57 0.9×	25 0.4×	31	629
Bruce A. Whitehead United States	9	338 1.1×	178 1.4×	68 0.7×	37 0.6×	10 0.2×	16	604
Petia Koprinkova‐Hristova Bulgaria	12	213 0.7×	88 0.7×	59 0.6×	27 0.5×	10 0.2×	61	445
Jianjun Wang China	13	116 0.4×	106 0.9×	113 1.1×	15 0.3×	22 0.4×	50	604
Luca Baldassarre Switzerland	10	136 0.5×	60 0.5×	16 0.2×	59 1.0×	36 0.6×	23	424
Sebastian Gerwinn Germany	12	83 0.3×	262 2.1×	48 0.5×	17 0.3×	16 0.3×	25	479
Zoltan Schreter Australia	4	187 0.6×	174 1.4×	29 0.3×	27 0.5×	6 0.1×	6	449
Gary M. Kuhn United States	12	352 1.2×	136 1.1×	47 0.5×	27 0.5×	4 0.1×	22	594
W. H. Huggins United States	15	96 0.3×	155 1.3×	113 1.1×	37 0.6×	18 0.3×	32	620
H.-U. Bauer Germany	13	397 1.3×	222 1.8×	48 0.5×	31 0.5×	6 0.1×	25	715

Countries citing papers authored by Malte Kuß

Since Specialization

Citations

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

Fields of papers citing papers by Malte Kuß

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Malte Kuß

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

All Works

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11 of 11 papers shown

1.

Kuß, Malte, et al.. (2006). Nonstationary Gaussian Process Regression using a Latent Extension of the Input Space. MPG.PuRe (Max Planck Society). 18 indexed citations

2.

Kuß, Malte. (2005). Bayesian inference for psychometric functions. Journal of Visualization. 5(8). 478–492. 13 indexed citations

3.

Kuß, Malte & Carl Edward Rasmussen. (2005). Assessing Approximate Inference for Binary Gaussian Process Classification. Journal of Machine Learning Research. 6(57). 1679–1704. 167 indexed citations

4.

Kuß, Malte & Carl Edward Rasmussen. (2005). Assessing Approximations for Gaussian Process Classification. Max Planck Institute for Plasma Physics. 18. 699–706. 16 indexed citations

5.

Kuß, Malte, Frank Jäkel, & Felix A. Wichmann. (2005). Bayesian inference for psychometric functions. Journal of Vision. 5(5). 8–8. 111 indexed citations

6.

Kuß, Malte, Frank Jäkel, & Felix A. Wichmann. (2005). Approximate Bayesian Inference for Psychometric Functions using MCMC Sampling. MPG.PuRe (Max Planck Society). 2 indexed citations

7.

Kuß, Malte, et al.. (2005). Approximate inference for robust Gaussian process regression. Cambridge University Engineering Department Publications Database. 10 indexed citations

8.

Eichhorn, J, Andreas S. Tolias, Alexander Zien, et al.. (2003). Prediction on Spike Data Using Kernel Algorithms. Cambridge University Engineering Department Publications Database. 16. 1367–1374. 19 indexed citations

9.

Kuß, Malte. (2003). The Geometry Of Kernel Canonical Correlation Analysis. MPG.PuRe (Max Planck Society). 61 indexed citations

10.

Kuß, Malte & Carl Edward Rasmussen. (2003). Gaussian Processes in Reinforcement Learning. 16. 751–758. 114 indexed citations

11.

Kuß, Malte. (2002). Nonlinear Multivariate Analysis with Geodesic Kernels. MPG.PuRe (Max Planck Society). 1 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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