Lars Buesing's Homepage
Office Address
Institute for Theoretical Computer Science
Graz University of Technology
Inffeldgasse 16b/1
A-8010 Graz, Austria
Phone: +43-3168735842
Email: lars@igi.tugraz.at
I'm a PhD student in the
lab for theoretical computer science
of
Prof. Maass
at the Graz University of Technology, Austria.
My research mainly focuses on recurrent neural networks and learning with spiking neurons. But I'm also interested in machine learning, dynamical systems, statistics...
Peer-Reviewed Publications
- L. Buesing, and W. Maass.
A spiking neuron as Information Bottleneck.
Neural Computation, in press 2010
preprint
- Claudia Clopath, Lars Buesing, Eleni Vasilaki, Wulfram Gerstner
Connectivity reflects coding: a model of voltage-based STDP with homeostasis
Nature Neuroscience 2010, doi:10.1038/nn.2479
link
- B. Schrauwen, L. Buesing, and R. Legenstein.
On computational power and the order-chaos phase transition in reservoir computing.
In Proc. of NIPS 2008, Advances in Neural Information Processing Systems, volume 21. MIT Press, 2009.
*Student Paper Award, Honorable Mentions*
paper
- L. Buesing, B. Schrauwen, and R. Legenstein.
Connectivity, dynamics, and memory
in reservoir computing with binary and analog neurons.
Neural Computation, in press 2009
preprint
- C. Clopath, L. Ziegler, E. Vasilaki, L. Buesing, and W. Gerstner.
Tag-trigger-consolidation:
A model of early and late long-term-potentiation and depression.
PLOS Computational Biology, 4(12):e1000248, 2008.
paper
-
L. Buesing and W. Maass.
Simplified rules and theoretical analysis for information
bottleneck optimization and PCA with spiking neurons.
In Proc. of NIPS 2007,
Advances in Neural Information Processing Systems, volume 20. MIT Press, 2008.
paper
- E. Muller, L. Buesing, J. Schemmel, and K. Meier.
Spike-frequency adapting neural
ensembles: Beyond mean adaptation and renewal theories.
Neural Computation, 19(11), 2007.
preprint