58 citations · 67 across the 3 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2023
Separable Gaussian Neural Networks: Structure, Analysis, and Function Approximations
Siyuan Xing, Jianqiao Sun
The Gaussian-radial-basis function neural network (GRBFNN) has been a popular choice for interpolation and classification. However, it is computationally intensive when the dimensi…
cs.LG2019★ 9 cited
Automatic Model Selection for Neural Networks
David Laredo, Yulin Qin, Oliver Schütze +1
Neural networks and deep learning are changing the way that artificial intelligence is being done. Efficiently choosing a suitable network architecture and fine-tune its hyper-para…
cs.LG2019★ 58 cited
A Neural Network-Evolutionary Computational Framework for Remaining Useful Life Estimation of Mechanical Systems
David Laredo, Zhaoyin Chen, Oliver Schütze +1
This paper presents a framework for estimating the remaining useful life (RUL) of mechanical systems. The framework consists of a multi-layer perceptron and an evolutionary algorit…