477 citations · 1.4k across the 57 of their papers we have counts for
5 papers · 1 filter
Quaternion Convolutional Neural Networks for Detection and Localization of 3D Sound Events
Danilo Comminiello, Marco Lella, Simone Scardapane +1
Learning from data in the quaternion domain enables us to exploit internal dependencies of 4D signals and treating them as a single entity. One of the models that perfectly suits w…
Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello +2
Gated recurrent neural networks have achieved remarkable results in the analysis of sequential data. Inside these networks, gates are used to control the flow of information, allow…
Reservoir computing approaches for representation and classification of multivariate time series
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse +1
Classification of multivariate time series (MTS) has been tackled with a large variety of methodologies and applied to a wide range of scenarios. Reservoir Computing (RC) provides…
Improving Graph Convolutional Networks with Non-Parametric Activation Functions
Simone Scardapane, Steven Van Vaerenbergh, Danilo Comminiello +1
Graph neural networks (GNNs) are a class of neural networks that allow to efficiently perform inference on data that is associated to a graph structure, such as, e.g., citation net…
Complex-valued Neural Networks with Non-parametric Activation Functions
Simone Scardapane, Steven Van Vaerenbergh, Amir Hussain +1
Complex-valued neural networks (CVNNs) are a powerful modeling tool for domains where data can be naturally interpreted in terms of complex numbers. However, several analytical pro…