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Number of items at this level (without sub-levels): 30.


Collaboration, Open Science (2015):
Estimating the reproducibility of psychological science.
In: Science, 349, p. 943. DOI: 10.1126/science.aac4716,

Cooke, T. ; Jäkel, F. ; Wallraven, C. ; Bülthoff, H. (2007):
Multimodal Similarity and Categorization of Novel, Three-Dimensional Objects.
In: Neuropsychologia, 45, pp. 484-495. DOI: 10.1016/j.neuropsychologia.2006.02.009,


Fleming, R. ; Jäkel, F. ; Maloney, L. T. (2011):
Visual Perception of Thick Transparent Materials.
In: Psychological Science, 22, pp. 812-820. DOI: 10.1177/0956797611408734,


Gershman, S. J. ; Tenenbaum, J. ; Jäkel, F. (2016):
Discovering hierarchical motion structure.
In: Vision Research, 126, pp. 232-241. DOI: 10.1016/j.visres.2015.03.004,

Gershman, S. J. ; Jäkel, F. ; Tenenbaum, J. B. (2013):
Bayesian Vector Analysis and the Perception of Hierarchical Motion.
Austin, TX, Cognitive Science Society, Proceedings of the 35th Annual Conference of the Cognitive Science Society / ed. by M. Knauff ; M. Plauen ; N. Sebanz ; I. Wachsmuth, Austin, TX, [Conference or Workshop Item]

Görür, D. ; Jäkel, F. ; Rasmussen, C. E. (2006):
A Choice Model with Infinitely Many Latent Features.
pp. 8-15, Pittsburgh, PA, Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA, [Conference or Workshop Item]


Hummel, P. A. ; Jäkel, F. ; Lange, S. ; Mertelsmann, R.
Cox, M. ; Funk, P. ; Begum, S. (eds.) (2018):
A Textual Recommender System for Clinical Data.
In: Lecture Notes in Computer Science, pp. 140-152, Sitockholm (Sweden), International Conference on Case-Based Reasoning 2018, [Conference or Workshop Item]


Jäkel, F. ; Worm, Oliver ; Lange, Sascha ; Mertelsmann, Roland (2018):
A stochastic model of myeloid cell lineages in hematopoiesis and pathway mutations in acute myeloid leukemia.
In: PloS one, 13 (10), pp. 1-25. ISSN 1932-6203,
DOI: 10.1371/journal.pone.0204393,

Jäkel, F. ; Singh, M. ; Wichmann, F. A. ; Herzog, M. H. (2016):
An overview of quantitative approaches in Gestalt perception.
In: Vision Research, 126, pp. 3-8. DOI: 10.1016/j.visres.2016.06.004,

Jäkel, F. ; Liu, M. (2016):
On interactivity in probabilistic pragmatics: yet another rational analysis of scalar implicatures.
In: Zeitschrift für Sprachwissenschaft, 35 (1), pp. 69-87. DOI: 10.1515/zfs-2016-0005,

Jäkel, F. ; Schreiber, C. (2013):
Introspection in Problem Solving.
In: Journal of Problem Solving, 6 (1), pp. 20-33. DOI: 10.7771/1932-6246.1131,

Jäkel, F. ; Meyer, U. (2013):
Kategorisierung und Begriffe.
In: Handbuch Kognitionswissenschaft / hrsg. von A. Stephan ; S. Walter, Stuttgart, Metzler, [Book Section]

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2009):
Does Cognitive Science Need Kernels.
In: Trends in Cognitive Sciences, 13, pp. 381-388. DOI: 10.1016/j.tics.2009.06.002,

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2008):
Similarity, Kernels and the Triangle Inequality.
In: Journal of Mathematical Psychology, 52 (5), pp. 297-303. DOI: 10.1016/j.jmp.2008.03.001,

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2008):
Generalization and Similarity in Exemplar Models of Categorization: Insights from Machine Learning.
In: Psychonomic Bulletin & Review, 15 (2), pp. 256-271. DOI: 10.3758/PBR.15.2.256,

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2007):
A Tutorial on Kernel Methods for Categorization.
In: Journal of Mathematical Psychology, 51, pp. 343-358. DOI: 10.1016/j.jmp.2007.06.002,

Jäkel, F. ; Wichmann, F. A. (2006):
Spatial four-alternative forced-choice method is the preferred psychophysical method for naïve observers.
In: Journal of Vision, 6 (11), pp. 1307-1322. DOI: 10.1167/6.11.13,

Jäkel, F. ; Ernst, M. O.
Oakley, I. ; O'Modhrain, S. ; Newell, F. (eds.) (2003):
Learning to Combine Arbitrary Signals from Vision and Touch.
pp. 276-290, Trinity College Dublin and Media Lab Europe, Eurohaptics 2003 Conference Proceedings, [Conference or Workshop Item]


Kuss, M. ; Jäkel, F. ; Wichmann, F. A. (2005):
Bayesian Inference for Psychometric Functions.
In: Journal of Vision, 5, pp. 478-492. DOI: 10.1167/5.5.8,


León-Villagrá, P. ; Jäkel, F.
Knauff, M. ; Pauen, M. ; Sebanz, N. ; Wachsmuth, I. (eds.) (2013):
Categorization and Abstract Similarity in Chess.
Austin, TX, Annual Conference of the Cognitive Science Society 2013, Austin, TX, [Conference or Workshop Item]


Stoilova, V. V. ; Knauer, B. ; Berg, S. ; Rieber, E. ; Jäkel, F. ; Stüttgen, M. C. (2020):
Auditory cortex reflects goal-directed movement but is not necessary for behavioral adaptation in sound-cued reward tracking.
In: Journal of Neurophysiology, American Physiological Society, ISSN 0022-3077,
DOI: 10.1152/jn.00736.2019,

Schumacher, J. ; Wunderle, T. ; Fries, P. ; Jäkel, F. ; Pipa, G. (2015):
A Statistical Framework to Infer Delay and Direction of Information Flow from Measurements of Complex Systems.
In: Neural Computation, 27, pp. 1555-1608. [Article]

Stüttgen, M. C. ; Kasties, N. ; Lengersdorf, D. ; Starosta, S. ; Güntürkün, O. ; Jäkel, F. (2013):
Suboptimal criterion setting in a perceptual choice task with asymmetric reinforcement.
In: Behavioral Processes, 96, pp. 59-70. DOI: 10.1016/j.beproc.2013.02.014,

Stüttgen, M. C. ; Schwarz, C. ; Jäkel, F. (2011):
Mapping spikes to sensations.
In: Frontiers in Neuroscience, 125 (5), pp. 1-17. DOI: 10.3389/fnins.2011.00125,

Savova, V. ; Jäkel, F. ; Tenenbaum, J. B. (2009):
Grammar-based object representations in a scene parsing task.
pp. 857-862, Austin, TX, Cognitive Science Society, Proceedings of the 31st Annual Meeting of the Cognitive Science Society / ed. by N. Taatge ; H. van Rijnn, Austin, TX, [Conference or Workshop Item]

Storck, J. ; Jäkel, F. ; Deco, G. (2001):
Temporal clustering with spiking neurons and dynamic synapses: towards technological applications.
In: Neural Networks, 14 (3), pp. 275-285. DOI: 10.1016/S0893-6080(00)00101-5,


Wichmann, F. A. ; Jäkel, F. (2018):
Methods in Psychophysics.
In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience / ed. by J.T. Wixted ; E.J. Wagenmakers, pp. 265-306, [Book Section]


Zednik, C. ; Jäkel, F. (2019):
Descending Marr’s levels: Standard observers are no panacea.
In: Behavioral and Brain Sciences, 41, pp. 43-44. [Article]

Zednik, C. ; Jäkel, F. (2016):
Bayesian reverse-engineering considered as a research strategy for cognitive science.
In: Synthese, pp. 3951-3985. DOI: 10.1007/s11229-016-1180-3,

Zednik, C. ; Jäkel, F. (2014):
How does Bayesian reverse-engineering work?
pp. 666-671, Austin, TX, Cognitive Science Society, Proceedings of the 36th Annual Conference of the Cognitive Science Society / ed. by P. Bello ; M. Guarini ; M. McShane ; B. Scasselati, Austin, TX, [Conference or Workshop Item]

This list was generated on Thu Jan 20 01:22:59 2022 CET.