Random Neural Networks — Erol Gelenbe / Serious Science @SeriousScience
Random Neural Networks — Erol Gelenbe / Serious Science  @SeriousScience
Uploaded June 2020 | Updated September 2026, 1 week ago
Computer scientist Erol Gelenbe on the communication of neurons, mathematical properties of the random neural networks and how can they be applied.

Read the full text on our website: serious-science.org/random-neural-networks-9974

'It was shown that this model has the property of universal approximation so that it could approximate continuous and bounded functions. This is very useful. Every time we use this beautiful mathematical properties to simplify the computations so that it is much faster to compute with a random neural network than it is with an ordinary deep learning system.'

Erol Gelenbe, Professor in Computer and Communication Networks, Imperial College London

Neural Networks: serious-science.org/neural-networks-9479
Computational Modeling of the Brain: serious-science.org/computational-modeling-of-the-brain-7557

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Random Neural Networks — Erol Gelenbe / Serious Science
Serious Science |

Random Neural Networks — Erol Gelenbe / Serious Science

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