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1
Introduction
2
Implications
3
plasticity
4
noise
5
Rewiring
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Analysis
7
Rewardbased learning
8
Experiments
9
Dynamics of Parameters
10
Initial Learning
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Conclusions
12
Questions
Description:
Explore dynamic neural network structures through stochastic rewiring in this 47-minute lecture by Robert Legenstein from Graz University of Technology. Delve into computational theories of the brain, covering topics such as plasticity, noise, rewiring analysis, and reward-based learning. Examine the dynamics of parameters and initial learning processes in neural networks. Gain insights into the implications of stochastic rewiring for understanding brain function and developing more efficient artificial neural networks.

Dynamic Neural Network Structures Through Stochastic Rewiring

Simons Institute
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