This paper gives a theoretic analysis based on information geometry. By studying the dual manifold architecture for modular NN and hierarchical NN and analyzing ...

In this paper we give an analysis based on information geometry and propose a knowledge- increasable model based on the idea of modular and hierarchical NN. The ...

In this paper, an extendable hierarchical large scale neural network model is developed based on the theoretical analysis of information geometry. In a ...

Yunhui Liu, Siwei Luo, Aijun Li, Hua Huang, Jinwei Wen: Information Geometry on Modular and Hierarchical Neural Network. APPT 2003: 577-581.

Apr 24, 2024 · In this section, we describe our neural method for modeling the appearances of complex materials exhibiting effects like shadows and specular ...

Missing: Modular Hierarchical

Here, we discuss different aspects of modularity and hierarchical modularity in relation to brain networks generated from neuroscience and neuroimaging data.

Jul 12, 2021 · Specifically, we build dedicated deep temporal architectures for time series classification, and explore the use of complex values in neural ...

We develop a modular deep encoder–decoder hierarchical (DeepEDH) convolutional neural network, a novel deep-learning-based surrogate modeling methodology.

May 17, 2023 · Recent advances in convolutional neural networks (CNNs) have enabled the accurate prediction of retinal responses to naturalistic stimuli, as ...