1 code implementation • 28 Jun 2023 • Anna Sergeevna Bosman, Andries Engelbrecht, Marde Helbig
Activation functions play a significant role in neural network design by enabling non-linearity.
1 code implementation • 29 Mar 2023 • Arné Schreuder, Anna Bosman, Andries Engelbrecht, Christopher Cleghorn
The process of training feedforward neural networks (FFNNs) can benefit from an automated process where the best heuristic to train the network is sought out automatically by means of a high-level probabilistic-based heuristic.
no code implementations • 14 Jun 2020 • Andreas Kamilaris, Andries Engelbrecht, Andreas Pitsillides, Francesc X. Prenafeta-Boldu
Intensive livestock production might have a negative environmental impact, by producing large amounts of animal manure, which, if not properly managed, can contaminate nearby water bodies with nutrient excess.
no code implementations • 5 Jun 2020 • Andreas Kamilaris, Andries Engelbrecht, Andreas Pitsillides, Francesc X. Prenafeta-Boldu
Intensive livestock production might have a negative environmental impact, by producing large amounts of animal excrements, which, if not properly managed, can contaminate nearby water bodies with nutrient excess.
no code implementations • 24 May 2019 • Anna Sergeevna Bosman, Andries Engelbrecht, Mardé Helbig
An increase in the hidden layer width is shown to effectively reduce the number of local minima, and simplify the shape of the global attractor.
no code implementations • 8 Jan 2019 • Anna Sergeevna Bosman, Andries Engelbrecht, Mardé Helbig
Quantification of the stationary points and the associated basins of attraction of neural network loss surfaces is an important step towards a better understanding of neural network loss surfaces at large.
