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- Dominik Thalmeier, Marvin Uhlmann, Hilbert J. Kappen, Raoul-Martin Memmesheimer
- PLoS computational biology
- 2016

Providing the neurobiological basis of information processing in higher animals, spiking neural networks must be able to learn a variety of complicated computations, including the generation of appropriate, possibly delayed reactions to inputs and the self-sustained generation of complex activity patterns, e.g. for locomotion. Many such computations require… (More)

- Dominik Thalmeier, Vicenç Gómez, Hilbert J. Kappen
- ArXiv
- 2016

The dynamical processes taking place on a network depend on its topology. Influencing the growth process of a network therefore has important implications on such dynamical processes. We formulate the problem of influencing the growth of a network as a stochastic optimal control problem in which a structural cost function penalizes undesired topologies. We… (More)

- Dominik Thalmeier, Jacob Halatek, Erwin Frey
- Proceedings of the National Academy of Sciences…
- 2016

Protein patterns are known to adapt to cell shape and serve as spatial templates that choreograph downstream processes like cell polarity or cell division. However, how can pattern-forming proteins sense and respond to the geometry of a cell, and what mechanistic principles underlie pattern formation? Current models invoke mechanisms based on dynamic… (More)

We formulate the problem of influencing the growth of a network as a stochastic optimal control problem in which a structural cost function penalizes undesired topologies. We approximate this control problem with a restricted class of control problems that can be solved using probabilistic inference methods. To deal with the increasing problem… (More)

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