Jan Drugowitsch

Orcid: 0000-0002-7846-0408

According to our database1, Jan Drugowitsch authored at least 16 papers between 2005 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2022
Projection Filtering With Observed State Increments With Applications in Continuous-Time Circular Filtering.
IEEE Trans. Signal Process., 2022

Is the information geometry of probabilistic population codes learnable?
Proceedings of the NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 2022

2021
Angular Path Integration by Projection Filtering with Increment Observations.
CoRR, 2021

2020
Adaptation Properties Allow Identification of Optimized Neural Codes.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019
VBLinLogit: Variational Bayesian linear and logistic regression.
J. Open Source Softw., 2019

2015
Simultaneous Learning and Filtering without Delusions: A Bayes-Optimal Derivation of Combining Predictive Inference and Adaptive Filtering.
Frontiers Comput. Neurosci., 2015

2014
Filtering Sensory Information with XCSF: Improving Learning Robustness and Robot Arm Control Performance.
Evol. Comput., 2014

Optimal decision-making with time-varying evidence reliability.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2012
Filtering sensory information with XCSF: improving learning robustness and control performance.
Proceedings of the Genetic and Evolutionary Computation Conference, 2012

2008
Design and Analysis of Learning Classifier Systems - A Probabilistic Approach
Studies in Computational Intelligence 139, Springer, ISBN: 978-3-540-79865-1, 2008

A formal framework and extensions for function approximation in learning classifier systems.
Mach. Learn., 2008

2007
Learning classifier systems from first principles : a probabilistic reformulation of learning classifier systems from the perspective of machine learning.
PhD thesis, 2007

Analysis and Improvements of the Classifier Error Estimate in XCSF.
Proceedings of the Learning Classifier Systems, 2007

A principled foundation for LCS.
Proceedings of the Genetic and Evolutionary Computation Conference, 2007

Mixing independent classifiers.
Proceedings of the Genetic and Evolutionary Computation Conference, 2007

2005
XCS with eligibility traces.
Proceedings of the Genetic and Evolutionary Computation Conference, 2005


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