Aug 31, 2020 · At its core, NEO aims to aid evolutionary search by eliciting a useful gradient from a surrogate model. Another possibility to improve ...
Sep 5, 2020 · We address this challenge by mapping the search process to a continuous space using recurrent neural networks.
This research deals with the initial investigations on the concept of a chaos-driven evolutionary algorithm Differential evolution. This paper is aimed at the ...
... Neuromemetic Evolutionary Optimization (NEO) to evolutionary synthesis of programs. Evaluation on a range of benchmarks suggests that NEO significantly ...
In this work, we present an improvement to this approach that enables rapid prototyping of new applications of spiking neural networks in neuromorphic systems.
Missing: Neuromemetic | Show results with:Neuromemetic
We present several case studies of how EONS can be used, including to train spiking neural networks for classification and control tasks, to train under ...
Missing: Neuromemetic | Show results with:Neuromemetic
Neuromemetic Evolutionary Optimization. Parallel Problem Solving from Nature – PPSN XVI, 2020, Volume 12269. ISBN : 978-3-030-58111-4. Paweł Liskowski ...
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Jun 18, 2020 · In this work, we present an improvement to this approach that enables rapid prototyping of new applications of spiking neural networks in neuromorphic systems.
Missing: Neuromemetic | Show results with:Neuromemetic
Duration: 1:07:13
Posted: Mar 21, 2023
Posted: Mar 21, 2023
Missing: Neuromemetic | Show results with:Neuromemetic
This paper presents an original method to automatically tune reconfigurable neuromimetic analog integrated circuits according to biological relevance. This ...