Johan Kwisthout
Johan Kwisthout
Full Professor, Radboud University Nijmegen, Donders Center for Cognition
Verified email at - Homepage
Cited by
Cited by
Community-based influence maximization in social networks under a competitive linear threshold model
A Bozorgi, S Samet, J Kwisthout, T Wareham
Knowledge-Based Systems 134, 149-158, 2017
Most probable explanations in Bayesian networks: Complexity and tractability
J Kwisthout
International Journal of Approximate Reasoning 52 (9), 1452-1469, 2011
Beta-and gamma-band activity reflect predictive coding in the processing of causal events
S van Pelt, L Heil, J Kwisthout, S Ondobaka, I van Rooij, H Bekkering
Social cognitive and affective neuroscience 11 (6), 973-980, 2016
Bayesian intractability is not an ailment that approximation can cure.
J Kwisthout, T Wareham, I Van Rooij
Cogn. Sci. 35 (5), 779-784, 2011
The necessity of bounded treewidth for efficient inference in Bayesian networks
JHP Kwisthout, HL Bodlaender, LC van der Gaag
ECAI 2010, 237-242, 2010
Cognition and intractability: A guide to classical and parameterized complexity analysis
I Van Rooij, M Blokpoel, J Kwisthout, T Wareham
Cambridge University Press, 2019
To be precise, the details don’t matter: On predictive processing, precision, and level of detail of predictions
J Kwisthout, H Bekkering, I Van Rooij
Brain and cognition 112, 84-91, 2017
Intentional communication: Computationally easy or difficult?
I Van Rooij, J Kwisthout, M Blokpoel, J Szymanik, T Wareham, I Toni
Frontiers in Human Neuroscience 5, 52, 2011
Bridging the gap between theory and practice of approximate Bayesian inference
J Kwisthout, I Van Rooij
Cognitive Systems Research 24, 2-8, 2013
Joint attention and language evolution
J Kwisthout, P Vogt, P Haselager, T Dijkstra
Connection Science 20 (2-3), 155-171, 2008
Structural properties as proxy for semantic relevance in RDF graph sampling
L Rietveld, R Hoekstra, S Schlobach, C Guéret
International Semantic Web Conference, 81-96, 2014
Perception is in the details: A predictive coding account of the psychedelic phenomenon
S Pink-Hashkes, I van Rooij, J Kwisthout
Proceedings of the Annual Meeting of the Cognitive Science Society 39, 2017
Computational resource demands of a predictive Bayesian brain
J Kwisthout, I Van Rooij
Computational Brain & Behavior 3 (2), 174-188, 2020
Rational analysis, intractability, and the prospects of ‘as if’-explanations
I van Rooij, CD Wright, J Kwisthout, T Wareham
Synthese 195, 491-510, 2018
Can infants' sense of agency be found in their behavior? Insights from babybot simulations of the mobile-paradigm
L Zaadnoordijk, M Otworowska, J Kwisthout, S Hunnius
Cognition 181, 58-64, 2018
The computational complexity of probabilistic networks
JHP Kwisthout
Utrecht University, 2009
When can predictive brains be truly Bayesian?
M Blokpoel, J Kwisthout, I van Rooij
Frontiers in psychology 3, 406, 2012
The computational complexity of sensitivity analysis and parameter tuning
J Kwisthout, LC Van Der Gaag
arXiv preprint arXiv:1206.3265, 2012
A computational-level explanation of the speed of goal inference
M Blokpoel, J Kwisthout, TP van der Weide, T Wareham, I van Rooij
Journal of Mathematical Psychology 57 (3-4), 117-133, 2013
On the computational power and complexity of spiking neural networks
J Kwisthout, N Donselaar
Proceedings of the 2020 Annual Neuro-Inspired Computational Elements …, 2020
The system can't perform the operation now. Try again later.
Articles 1–20