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- Wolfgang Maass, Thomas NatschlÃ¤ger, Henry Markram
- Neural Computation
- 2002

A key challenge for neural modeling is to explain how a continuous stream of multimodal input from a rapidly changing environment can be processed by stereotypical recurrent circuits ofâ€¦ (More)

- Dorit S. Hochbaum, Wolfgang Maass
- J. ACM
- 1985

A unified and powerful approach is presented for devising polynomial approximation schemes for many strongly NP-complete problems. Such schemes consist of families of approximation algorithms forâ€¦ (More)

- Wolfgang Maass
- Electronic Colloquium on Computational Complexity
- 1996

-The computational power of formal models for networks of spiking neurons is compared with that of other neural network models based on McCulloch Pitts neurons (i.e., threshold gates), respectively,â€¦ (More)

- Dean V. Buonomano, Wolfgang Maass
- Nature Reviews Neuroscience
- 2009

A conspicuous ability of the brain is to seamlessly assimilate and process spatial and temporal features of sensory stimuli. This ability is indispensable for the recognition of natural stimuli. Yet,â€¦ (More)

- Bernhard Nessler, Michael Pfeiffer, Lars Buesing, Wolfgang Maass
- PLoS Computational Biology
- 2013

The principles by which networks of neurons compute, and how spike-timing dependent plasticity (STDP) of synaptic weights generates and maintains their computational function, are unknown. Precedingâ€¦ (More)

- Robert A. Legenstein, Wolfgang Maass
- Neural Networks
- 2007

We analyze in this article the significance of the edge of chaos for real-time computations in neural microcircuit models consisting of spiking neurons and dynamic synapses. We find that the edge ofâ€¦ (More)

- Wolfgang Maass
- Neural Computation
- 1997

We show that networks of relatively realistic mathematical models for biological neurons in principle can simulate arbitrary feedforward sigmoidal neural nets in a way that has previously not beenâ€¦ (More)

- Wolfgang Maass
- Neural Computation
- 1994

We investigate the computational power of a formal model for networks of spiking neurons. It is shown that simple operations on phase differences between spike-trains provide a very powerfulâ€¦ (More)

- Lars Buesing, Johannes Bill, Bernhard Nessler, Wolfgang Maass
- PLoS Computational Biology
- 2011

The organization of computations in networks of spiking neurons in the brain is still largely unknown, in particular in view of the inherently stochastic features of their firing activity and theâ€¦ (More)

In the preceding chapter a number of mathematical models for spiking neurons were introduced. Spiking neurons differ in essential aspects from the familiar computational units of common neuralâ€¦ (More)