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Jan Drugowitsch
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2020 – today
- 2022
- [j5]Anna Kutschireiter
, Luke I. Rast, Jan Drugowitsch
Projection Filtering With Observed State Increments With Applications in Continuous-Time Circular Filtering. IEEE Trans. Signal Process. 70: 686-700 (2022) - [c9]John J. Vastola, Zach Cohen, Jan Drugowitsch:
Is the information geometry of probabilistic population codes learnable? NeurReps 2022: 258-277 - 2021
- [i1]Anna Kutschireiter, Luke I. Rast, Jan Drugowitsch:
Angular Path Integration by Projection Filtering with Increment Observations. CoRR abs/2102.09650 (2021) - 2020
- [c8]Luke I. Rast, Jan Drugowitsch:
Adaptation Properties Allow Identification of Optimized Neural Codes. NeurIPS 2020
2010 – 2019
- 2019
- [j4]Jan Drugowitsch
VBLinLogit: Variational Bayesian linear and logistic regression. J. Open Source Softw. 4(38): 1359 (2019) - 2015
- [j3]Jan Kneissler, Jan Drugowitsch, Karl J. Friston
Simultaneous Learning and Filtering without Delusions: A Bayes-Optimal Derivation of Combining Predictive Inference and Adaptive Filtering. Frontiers Comput. Neurosci. 9: 47 (2015) - 2014
- [j2]Jan Kneissler, Patrick O. Stalph, Jan Drugowitsch, Martin V. Butz
Filtering Sensory Information with XCSF: Improving Learning Robustness and Robot Arm Control Performance. Evol. Comput. 22(1): 139-158 (2014) - [c7]Jan Drugowitsch, Rubén Moreno-Bote, Alexandre Pouget:
Optimal decision-making with time-varying evidence reliability. NIPS 2014: 748-756 - 2012
- [c6]Jan Kneissler, Patrick O. Stalph, Jan Drugowitsch, Martin V. Butz
Filtering sensory information with XCSF: improving learning robustness and control performance. GECCO 2012: 871-878 - 2010
- [e1]Jaume Bacardit
Learning Classifier Systems - 11th International Workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008, and 12th International Workshop, IWLCS 2009, Montreal, QC, Canada, July 9, 2009, Revised Selected Papers. Lecture Notes in Computer Science 6471, Springer 2010, ISBN 978-3-642-17507-7 [contents]
2000 – 2009
- 2008
- [b2]Jan Drugowitsch:
Design and Analysis of Learning Classifier Systems - A Probabilistic Approach. Studies in Computational Intelligence 139, Springer 2008, ISBN 978-3-540-79865-1, pp. 1-239 [contents] - [j1]Jan Drugowitsch, Alwyn Barry:
A formal framework and extensions for function approximation in learning classifier systems. Mach. Learn. 70(1): 45-88 (2008) - 2007
- [b1]Jan Drugowitsch:
Learning classifier systems from first principles : a probabilistic reformulation of learning classifier systems from the perspective of machine learning. University of Bath, Somerset, UK, 2007 - [c5]Jan Drugowitsch, Alwyn Barry:
Mixing independent classifiers. GECCO 2007: 1596-1603 - [c4]Jan Drugowitsch, Alwyn Barry:
A principled foundation for LCS. GECCO (Companion) 2007: 2675-2680 - [c3]Jan Drugowitsch, Alwyn Barry:
A Principled Foundation for LCS. IWLCS 2007: 77-95 - [c2]Daniele Loiacono, Jan Drugowitsch, Alwyn Barry, Pier Luca Lanzi:
Analysis and Improvements of the Classifier Error Estimate in XCSF. IWLCS 2007: 117-135 - 2005
- [c1]Jan Drugowitsch, Alwyn Barry:
XCS with eligibility traces. GECCO 2005: 1851-1858
Coauthor Index
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