Abstract: Radial basis function neural networks (RBFNNs) have been widely used in data modeling and prediction in recent years. However, an RBFNN does not perform well when it comes to practical ...

Learn how backpropagation works by building it from scratch in Python! This tutorial explains the math, logic, and coding behind training a neural network, helping you truly understand how deep ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Abstract: The radial basis function neural network (RBFNN) is a learning model with better generalization ability, which attracts much attention in nonlinear system identification. Compared with the ...

Hi, thank you for this great package! I was wondering whether it would be straightforward to combine this package with Lux.jl to build a radial basis function network (RBFN). Has anyone tried that?

The Network for Movement and Physical Function held its first retreat in collaboration with Bone Hub, sponsored by Promobilia on November 10 - 11, 2025 at Djurönäset Conference Center. In total, 66 ...

ABSTRACT: We solve numerically an eigenvalue elliptic partial differential equation (PDE) ranging from two to six dimensions using the generalized multiquadric (GMQ) radial basis functions (RBFs). Two ...

1 Central Institute of Mental Health, Department of Psychiatry and Psychotherapy, Germany 2 Bernstein Center for Computational Neuroscience Heidelberg-Mannheim, Germany Hippocampal-prefrontal ...

Research on how we move is critical to understand and treat a variety of medical conditions, from musculoskeletal disorders due to injury, work or genetic disorders to movement problems in ...

Recent work has established an alternative to traditional multi-layer perceptron neural networks in the form of Kolmogorov-Arnold Networks (KAN). The general KAN framework uses learnable activation ...