 | 2009 |
|---|
| 18 |       | Stefan Klampfl,
Robert A. Legenstein,
Wolfgang Maass:
Spiking Neurons Can Learn to Solve Information Bottleneck Problems and Extract Independent Components.
Neural Computation 21(4): 911-959 (2009) |
| 2008 |
|---|
| 17 | | Benjamin Schrauwen,
Lars Buesing,
Robert A. Legenstein:
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing.
NIPS 2008: 1425-1432 |
| 16 | | Robert A. Legenstein,
Wolfgang Maass:
On the Classification Capability of Sign-Constrained Perceptrons.
Neural Computation 20(1): 288-309 (2008) |
| 2007 |
|---|
| 15 | | Robert A. Legenstein,
Dejan Pecevski,
Wolfgang Maass:
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity.
NIPS 2007 |
| 14 | | Robert A. Legenstein,
Wolfgang Maass:
Edge of chaos and prediction of computational performance for neural circuit models.
Neural Networks 20(3): 323-334 (2007) |
| 2006 |
|---|
| 13 | | Stefan Klampfl,
Robert A. Legenstein,
Wolfgang Maass:
Information Bottleneck Optimization and Independent Component Extraction with Spiking Neurons.
NIPS 2006: 713-720 |
| 2005 |
|---|
| 12 | | Robert A. Legenstein,
Wolfgang Maass:
A Criterion for the Convergence of Learning with Spike Timing Dependent Plasticity.
NIPS 2005 |
| 11 | | Robert A. Legenstein,
Wolfgang Maass:
Wire length as a circuit complexity measure.
J. Comput. Syst. Sci. 70(1): 53-72 (2005) |
| 10 | | Robert A. Legenstein,
Christian Naeger,
Wolfgang Maass:
What Can a Neuron Learn with Spike-Timing-Dependent Plasticity?
Neural Computation 17(11): 2337-2382 (2005) |
| 2004 |
|---|
| 9 | | Nils Bertschinger,
Thomas Natschläger,
Robert A. Legenstein:
At the Edge of Chaos: Real-time Computations and Self-Organized Criticality in Recurrent Neural Networks.
NIPS 2004 |
| 8 | | Wolfgang Maass,
Robert A. Legenstein,
Nils Bertschinger:
Methods for Estimating the Computational Power and Generalization Capability of Neural Microcircuits.
NIPS 2004 |
| 2002 |
|---|
| 7 | | Wolfgang Maass,
Robert A. Legenstein,
Henry Markram:
A New Approach towards Vision Suggested by Biologically Realistic Neural Microcircuit Models.
Biologically Motivated Computer Vision 2002: 282-293 |
| 6 |  | Robert A. Legenstein,
Wolfgang Maass:
Neural circuits for pattern recognition with small total wire length.
Theor. Comput. Sci. 287(1): 239-249 (2002) |
| 2001 |
|---|
| 5 | | Robert A. Legenstein,
Wolfgang Maass:
Optimizing the Layout of a Balanced Tree
Electronic Colloquium on Computational Complexity (ECCC) 8(069): (2001) |
| 4 | | Robert A. Legenstein,
Wolfgang Maass:
Total Wire Length as a Salient Circuit Complexity Measure for Sensory Processing
Electronic Colloquium on Computational Complexity (ECCC) 8(070): (2001) |
| 3 | | Robert A. Legenstein,
Wolfgang Maass:
Neural Circuits for Pattern Recognition with Small Total Wire Length
Electronic Colloquium on Computational Complexity (ECCC) 8(071): (2001) |
| 2 | | Robert A. Legenstein:
On the Complexity of Knock-knee Channel-Routing with 3-Terminal Nets
Electronic Colloquium on Computational Complexity (ECCC)(076): (2001) |
| 2000 |
|---|
| 1 | | Robert A. Legenstein,
Wolfgang Maass:
Foundations for a Circuit Complexity Theory of Sensory Processing.
NIPS 2000: 259-265 |
