Frank Jäkel

1.2k total citations
36 papers, 727 citations indexed

About

Frank Jäkel is a scholar working on Cognitive Neuroscience, Artificial Intelligence and Developmental and Educational Psychology. According to data from OpenAlex, Frank Jäkel has authored 36 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Cognitive Neuroscience, 14 papers in Artificial Intelligence and 8 papers in Developmental and Educational Psychology. Recurrent topics in Frank Jäkel's work include Visual perception and processing mechanisms (9 papers), Neural dynamics and brain function (6 papers) and Behavioral and Psychological Studies (4 papers). Frank Jäkel is often cited by papers focused on Visual perception and processing mechanisms (9 papers), Neural dynamics and brain function (6 papers) and Behavioral and Psychological Studies (4 papers). Frank Jäkel collaborates with scholars based in Germany, United States and Switzerland. Frank Jäkel's co-authors include Felix A. Wichmann, Bernhard Schölkopf, Malte Kuß, Roland W. Fleming, Laurence T. Maloney, T Cooke, HH Bülthoff, Christian Wallraven, Samuel J. Gershman and Joshua B. Tenenbaum and has published in prestigious journals such as PLoS ONE, Trends in Cognitive Sciences and Journal of Neurophysiology.

In The Last Decade

Frank Jäkel

31 papers receiving 700 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Frank Jäkel Germany	14	408	160	126	100	79	36	727
Alexander A. Petrov United States	12	842 2.1×	136 0.8×	231 1.8×	78 0.8×	91 1.2×	48	1.1k
William A. Simpson United Kingdom	17	472 1.2×	103 0.6×	73 0.6×	69 0.7×	94 1.2×	63	840
Yoav Cohen United States	14	614 1.5×	58 0.4×	132 1.0×	144 1.4×	111 1.4×	25	976
Emanuel Leeuwenberg Netherlands	16	665 1.6×	91 0.6×	201 1.6×	183 1.8×	210 2.7×	31	873
David C. Brogan United States	14	484 1.2×	112 0.7×	218 1.7×	187 1.9×	73 0.9×	34	1.1k
Shimon Edelman Israel	11	1.4k 3.3×	124 0.8×	221 1.8×	273 2.7×	123 1.6×	15	1.6k
Hans Buffart Netherlands	9	427 1.0×	96 0.6×	101 0.8×	112 1.1×	130 1.6×	12	602
Richard Romero United States	7	634 1.6×	64 0.4×	66 0.5×	139 1.4×	46 0.6×	10	810
Sergei Gepshtein United States	19	1.1k 2.7×	53 0.3×	326 2.6×	161 1.6×	256 3.2×	49	1.4k
Peter A. van der Helm Netherlands	23	1.1k 2.8×	136 0.8×	309 2.5×	307 3.1×	307 3.9×	50	1.6k

Countries citing papers authored by Frank Jäkel

Since Specialization

Citations

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

Fields of papers citing papers by Frank Jäkel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank Jäkel

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

All Works

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20 of 20 papers shown

Jäkel, Frank, et al.. (2025). Stimulus uncertainty and relative reward rates determine adaptive responding in perceptual decision-making. PLoS Computational Biology. 21(5). e1012636–e1012636.

Jäkel, Frank, et al.. (2024). From human explanations to explainable AI: Insights from constrained optimization. Cognitive Systems Research. 88. 101297–101297. 2 indexed citations

Stüttgen, Maik C., et al.. (2024). Reconciling Signal-Detection Models of Criterion Learning with the Generalized Matching Law. Computational Brain & Behavior. 8(1). 111–133. 1 indexed citations

Stüttgen, Maik C., et al.. (2024). Influence of reinforcement and its omission on trial‐by‐trial changes of response bias in perceptual decision making. Journal of the Experimental Analysis of Behavior. 121(3). 294–313. 2 indexed citations

Balfanz, Dirk, et al.. (2024). An Evaluation of Situational Autonomy for Human-AI Collaboration in a Shared Workspace Setting. TUbilio (Technical University of Darmstadt). 1–17. 4 indexed citations

Jäkel, Frank, et al.. (2024). Connecting process models to response times through Bayesian hierarchical regression analysis. Behavior Research Methods. 56(7). 6951–6966. 1 indexed citations

Jäkel, Frank, et al.. (2024). SimplifEx: Simplifying and Explaining Linear Programs. Cognitive Systems Research. 88. 101298–101298. 1 indexed citations

Rothkopf, Constantin A., et al.. (2023). Parameter estimation for a bivariate beta distribution with arbitrary beta marginals and positive correlation. METRON. 81(2). 163–180. 1 indexed citations

Rothkopf, Constantin A., et al.. (2023). A normative model for Bayesian combination of subjective probability estimates. Judgment and Decision Making. 18.

10.

Berg, Stephanie, et al.. (2020). Auditory cortex reflects goal-directed movement but is not necessary for behavioral adaptation in sound-cued reward tracking. Journal of Neurophysiology. 124(4). 1056–1071. 8 indexed citations

11.

Jäkel, Frank, et al.. (2018). A stochastic model of myeloid cell lineages in hematopoiesis and pathway mutations in acute myeloid leukemia. PLoS ONE. 13(10). e0204393–e0204393. 4 indexed citations

12.

Jäkel, Frank, Manish Singh, Felix A. Wichmann, & Michael H. Herzog. (2016). An overview of quantitative approaches in Gestalt perception. Vision Research. 126. 3–8. 34 indexed citations

13.

Gershman, Samuel J., Joshua B. Tenenbaum, & Frank Jäkel. (2015). Discovering hierarchical motion structure. Vision Research. 126. 232–241. 30 indexed citations

14.

Gershman, Samuel J., Frank Jäkel, & Joshua B. Tenenbaum. (2013). Bayesian vector analysis and the perception of hierarchical motion. Cognitive Science. 35(35). 5 indexed citations

15.

Stüttgen, Maik C., et al.. (2013). Suboptimal criterion setting in a perceptual choice task with asymmetric reinforcement. Behavioural Processes. 96. 59–70. 13 indexed citations

16.

Jäkel, Frank, Bernhard Schölkopf, & Felix A. Wichmann. (2008). Generalization and similarity in exemplar models of categorization: Insights from machine learning. Psychonomic Bulletin & Review. 15(2). 256–271. 46 indexed citations

17.

Cooke, T, Frank Jäkel, Christian Wallraven, & HH Bülthoff. (2006). Multimodal similarity and categorization of novel, three-dimensional objects. Neuropsychologia. 45(3). 484–495. 64 indexed citations

18.

Jäkel, Frank & Felix A. Wichmann. (2006). Spatial four-alternative forced-choice method is the preferred psychophysical method for naive observers. Journal of Vision. 6(11). 13–13. 98 indexed citations

19.

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

20.

Jäkel, Frank, et al.. (2001). Temporal clustering with spiking neurons and dynamic synapses: towards technological applications. Neural Networks. 14(3). 275–285. 9 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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