Neural Networks

Approximation and Optimization for Neural Networks

Gerrit Welper, Assistant Professor, Mathematics, University of Central Florida (UCF)

Mar 4, 16:00 - 17:00

Zoom Meeting 95807131415

Neural Networks optimization deep neural networks Finite element methods

In this talk, we consider new connections between the approximation and optimization of neural networks. Instead of relying on excessive over-parametrization to achieve zero training loss, we identify good minima by comparison with established approximation bounds.

Mapping Properties of Neural Networks and Inverse Problems

Prof. Matti Lassas, Applied Mathematics, University of Helsinki, Finland

Feb 12, 18:00 - 19:00

B1 L4 R4214

Neural Networks generative models

This talk will explore the injectivity and universal approximation properties of neural networks, focusing on one-to-one mappings and the approximation of probability measures using compositions of invertible flow networks and injective layers, with applications in inverse problems, imaging, and generative models.

Mohammed A Shukri

Consultant (former), King Abdullah University of Science and Technology

Neural Networks AI Python BLE communication

Technical Consultant at KAUST (King Abdullah University of Science and Technology).