Coen Visser

Coen Visser is a Research Fellow in the Department of Mathematics at the University of Oxford. His research focuses on computational methods for artificial neural networks, as evidenced by his publication titled 'PACMANN: Point Adaptive Collocation Method for Artificial Neural Networks,' co-authored with Alexander Heinlein and Bianca Giovanardi, and published in Computer Methods in Applied Mechanics and Engineering. His work contributes to the field of mathematical modeling and numerical analysis. Visser is affiliated with the Mathematical Institute at the Andrew Wiles Building, Radcliffe Observatory Quarter, Oxford.

Coen Visser is a researcher at the University of Oxford, specializing in scientific machine learning and high-performance computing. His work focuses on developing advanced computational methods to enhance the accuracy and efficiency of machine learning models in scientific applications. One of his notable contributions is the development of PACMANN, a point adaptive collocation method for artificial neural networks, which aims to improve the performance of neural networks in complex scientific simulations. His research bridges the gap between machine learning and computational science, offering novel approaches to tackle challenges in high-performance computing environments.