675 citations · 1.8k across the 55 of their papers we have counts for
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Training Deep Spiking Auto-encoders without Bursting or Dying Neurons through Regularization
Justus F. Hübotter, Pablo Lanillos, Jakub M. Tomczak
Spiking neural networks are a promising approach towards next-generation models of the brain in computational neuroscience. Moreover, compared to classic artificial neural networks…
Time Efficiency in Optimization with a Bayesian-Evolutionary Algorithm
Gongjin Lan, Jakub M. Tomczak, Diederik M. Roijers +1
Not all generate-and-test search algorithms are created equal. Bayesian Optimization (BO) invests a lot of computation time to generate the candidate solution that best balances th…
Differential Evolution with Reversible Linear Transformations
Jakub M. Tomczak, Ewelina Weglarz-Tomczak, Agoston E. Eiben
Differential evolution (DE) is a well-known type of evolutionary algorithms (EA). Similarly to other EA variants it can suffer from small populations and loose diversity too quickl…
Learning Directed Locomotion in Modular Robots with Evolvable Morphologies
Gongjin Lan, Matteo De Carlo, Fuda van Diggelen +3
We generalize the well-studied problem of gait learning in modular robots in two dimensions. Firstly, we address locomotion in a given target direction that goes beyond learning a…