Publications

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Group by: Publikationsjahr | Creator(s) | Item type
Jump to: 2019 | 2018 | 2016 | 2015 | 2014 | 2013 | 2011 | 2009 | 2008 | 2007 | 2006 | 2005 | 2003 | 2001
Number of items at this level: 29.

2019

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

2018

Hummel, P. A. ; Jäkel, F. ; Lange, S. ; Mertelsmann, R.
Cox, M. ; Funk, P. ; Begum, S. (Hrsg.) (2018):
A Textual Recommender System for Clinical Data.
In: International Conference on Case-Based Reasoning 2018, In: Lecture Notes in Computer Science, DOI: 10.1007/978-3-030-01081-2₁₀,
[Konferenzveröffentlichung]

Jäkel, Frank ; 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, S. 1-25, 13, (10), ISSN 1932-6203,
DOI: 10.1371/journal.pone.0204393,
[Article]

Wichmann, F. A. ; Jäkel, F.
Wixted, J. T. ; Wagenmakers, E. J. (Hrsg.) (2018):
Methods in Psychophysics.
In: Stevens' Handbook of Experimental Psychology and Cognitive Neuroscience, S. 265-306, [Online-Edition: https://www.wiley.com/en-us/Stevens%27+Handbook+of+Experimen...],
[Book section]

2016

Gershman, S. J. ; Tenenbaum, J. ; Jäkel, F. (2016):
Discovering hierarchical motion structure.
In: Vision Research, S. 232-241, (126), DOI: 10.1016/j.visres.2015.03.004,
[Online-Edition: http://dx.doi.org/10.1016/j.visres.2015.03.004],
[Article]

Jäkel, F. ; Liu, M. (2016):
On interactivity in probabilistic pragmatics: yet another rational analysis of scalar implicatures.
In: Zeitschrift für Sprachwissenschaft, S. 69-87, 35, (1), DOI: 10.1515/zfs-2016-0005,
[Online-Edition: https://doi.org/10.1515/zfs-2016-0005],
[Article]

Jäkel, F. ; Singh, M. ; Wichmann, F. A. ; Herzog, M. H. (2016):
An overview of quantitative approaches in Gestalt perception.
In: Vision Research, S. 3-8, (126), DOI: 10.1016/j.visres.2016.06.004,
[Online-Edition: https://doi.org/10.1016/j.visres.2016.06.004],
[Article]

Zednik, C. ; Jäkel, F. (2016):
Bayesian reverse-engineering considered as a research strategy for cognitive science.
In: Synthese, S. 3951-3985, DOI: 10.1007/s11229-016-1180-3,
[Online-Edition: https://doi.org/10.1007/s11229-016-1180-3],
[Article]

2015

Collaboration, Open Science (2015):
Estimating the reproducibility of psychological science.
In: Science, S. 943, 349, DOI: 10.1126/science.aac4716,
[Online-Edition: http://dx.doi.org/10.1126/science.aac4716],
[Article]

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, S. 1555-1608, 27, DOI: 10.1162/NECOa₀₀₇₅₆,
[Online-Edition: https://doi.org/10.1162/NECO_a_00756],
[Article]

2014

Zednik, C. ; Jäkel, F.
Bello, P. ; Guarini, M. ; McShane, M. ; Scasselati, B. (Hrsg.) (2014):
How does Bayesian reverse-engineering work?
Austin, TX, Cognitive Science Society, In: Proceedings of the 36th Annual Conference of the Cognitive Science Society, Austin, TX, [Online-Edition: https://mindmodeling.org/cogsci2014/papers/123/paper123.pdf],
[Konferenzveröffentlichung]

2013

Gershman, S. J. ; Jäkel, F. ; Tenenbaum, J. B.
Knauff, M. ; Pauen, M. ; Sebanz, N. ; Wachsmuth, I. (Hrsg.) (2013):
Bayesian Vector Analysis and the Perception of Hierarchical Motion.
Austin, TX, Cognitive Science Society, In: Proceedings of the 35th Annual Conference of the Cognitive Science Society, Austin, TX, [Online-Edition: http://mindmodeling.org/cogsci2013/papers/0112/paper0112.pdf],
[Konferenzveröffentlichung]

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

Jäkel, F. ; Schreiber, C. (2013):
Introspection in Problem Solving.
In: Journal of Problem Solving, S. 20-33, 6, (1), DOI: 10.7771/1932-6246.1131,
[Online-Edition: http://dx.doi.org/10.7771/1932-6246.1131],
[Article]

León-Villagrá, P. ; Jäkel, F.
Knauff, M. ; Pauen, M. ; Sebanz, N. ; Wachsmuth, I. (Hrsg.) (2013):
Categorization and Abstract Similarity in Chess.
Austin, TX, In: Annual Conference of the Cognitive Science Society 2013, Austin, TX, [Online-Edition: https://mindmodeling.org/cogsci2013/papers/0513/paper0513.pd...],
[Konferenzveröffentlichung]

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, S. 59-70, 96, DOI: 10.1016/j.beproc.2013.02.014,
[Online-Edition: https://doi.org/10.1016/j.beproc.2013.02.014],
[Article]

2011

Fleming, R. ; Jäkel, F. ; Maloney, L. T. (2011):
Visual Perception of Thick Transparent Materials.
In: Psychological Science, S. 812-820, 22, DOI: 10.1177/0956797611408734,
[Online-Edition: https://doi.org/10.1177/0956797611408734],
[Article]

Stüttgen, M. C. ; Schwarz, C. ; Jäkel, F. (2011):
Mapping spikes to sensations.
In: Frontiers in Neuroscience, S. 1-17, 5, (125), DOI: 10.3389/fnins.2011.00125,
[Online-Edition: https://doi.org/10.3389/fnins.2011.00125],
[Article]

2009

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2009):
Does Cognitive Science Need Kernels.
In: Trends in Cognitive Sciences, S. 381-388, 13, DOI: 10.1016/j.tics.2009.06.002,
[Online-Edition: https://doi.org/10.1016/j.tics.2009.06.002],
[Article]

Savova, V. ; Jäkel, F. ; Tenenbaum, J. B.
Taatgen, N. ; van Rijn, H. (Hrsg.) (2009):
Grammar-based object representations in a scene parsing task.
Austin, TX, Cognitive Science Society, In: Proceedings of the 31st Annual Meeting of the Cognitive Science Society, Austin, TX, [Online-Edition: http://csjarchive.cogsci.rpi.edu/proceedings/2009/papers/150...],
[Konferenzveröffentlichung]

2008

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

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2008):
Similarity, Kernels and the Triangle Inequality.
In: Journal of Mathematical Psychology, S. 297-303, 52, (5), DOI: 10.1016/j.jmp.2008.03.001,
[Online-Edition: https://doi.org/10.1016/j.jmp.2008.03.001],
[Article]

2007

Cooke, T. ; Jäkel, F. ; Wallraven, C. ; Bülthoff, H. (2007):
Multimodal Similarity and Categorization of Novel, Three-Dimensional Objects.
In: Neuropsychologia, S. 484-495, 45, DOI: 10.1016/j.neuropsychologia.2006.02.009,
[Online-Edition: https://doi.org/10.1016/j.neuropsychologia.2006.02.009],
[Article]

Jäkel, F. ; Schölkopf, B. ; Wichmann, F. A. (2007):
A Tutorial on Kernel Methods for Categorization.
In: Journal of Mathematical Psychology, S. 343-358, 51, DOI: 10.1016/j.jmp.2007.06.002,
[Online-Edition: https://doi.org/10.1016/j.jmp.2007.06.002],
[Article]

2006

Görür, D. ; Jäkel, F. ; Rasmussen, C. E. (2006):
A Choice Model with Infinitely Many Latent Features.
Pittsburgh, PA, In: Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA, [Online-Edition: https://dl.acm.org/citation.cfm?id=1143890],
[Konferenzveröffentlichung]

Jäkel, F. ; Wichmann, F. A. (2006):
Spatial four-alternative forced-choice method is the preferred psychophysical method for naïve observers.
In: Journal of Vision, S. 1307-1322, 6, (11), DOI: 10.1167/6.11.13,
[Online-Edition: http://journalofvision.org/6/11/13/],
[Article]

2005

Kuss, M. ; Jäkel, F. ; Wichmann, F. A. (2005):
Bayesian Inference for Psychometric Functions.
In: Journal of Vision, S. 478-492, 5, DOI: 10.1167/5.5.8,
[Online-Edition: https://doi.org/10.1167/5.5.8],
[Article]

2003

Jäkel, F. ; Ernst, M. O.
Oakley, I. ; O'Modhrain, S. ; Newell, F. (Hrsg.) (2003):
Learning to Combine Arbitrary Signals from Vision and Touch.
Trinity College Dublin and Media Lab Europe, In: Eurohaptics 2003 Conference Proceedings, [Konferenzveröffentlichung]

2001

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

This list was generated on Wed Oct 16 02:13:34 2019 CEST.