
In this webinar our two main features are as follows:
We will present the new idea of moving from the main neural network tools, the activation functions, to convolution integrals and singular integrals approximations. That is, the rare case of employing applied mathematics to treat theoretical ones.
We will introduce and also use the symmetrized neural network operators able to achieve supersonic speeds of convergence.
We will use a great variety of activation functions. Thus this webinar will present the original work by the speakers given at a very general level to cover a maximum number of different kinds of neural networks, covering ordinary, fractional and stochastic approximations. Univariate, fractional and multivariate approximations will also be presented. Iterated-sequential multi-layer approximations will be discussed as well.
Date: Friday, 10 April 2026
Time: 17:00 CEST to 18:45 CEST
Webinar ID: 845 9893 0293
Webinar Secretariat: journal.webinar@mdpi.com


In this section, you will find the recording of this webinar to watch. Re-watch and share with your colleagues!
In this webinar, the speakers introduced more intrinsic and sophisticated quantitative approximation properties of Activated Neural Network Operators in their convergence to the unit operator. The employed sigmoid activation functions either led to a cusp composite activation function of compact support or to a multi-composite activation function of infinite domain. Numerical results were also presented that proved the superiority of this method as well as our other method of symmetrization. Moreover, the speakers reported important sampling theory results and their connections to Neural Networks. Last, but not least, the topic of Multivariate Neural Network Operators—including inverse theorems and convergence rate in the Lp-norm—was covered.
Four incredible key speakers led the event, which was well attended by over 60 people worldwide. We would like to thank everyone who was involved in making this webinar a success, as well as the organizing company MDPI and the host personnel.
"Application and Perspectives of Neural Networks"
Edited by Dr. Ali Mehrabi
Deadine for manuscript submissions: 30 August 2026
"New Advances in Neural Networks and Applications"
Edited by Prof. Dr. Xinwei Cao, Dr. Ameer Tamoor Khan, and Prof. Dr. Predrag S. Stanimirović
Deadine for manuscript submissions: 29 April 2026