Steven Van Vaerenbergh | DeepAI

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∙ 07/13/2021

A Classification of Artificial Intelligence Systems for Mathematics Education

This chapter provides an overview of the different Artificial Intelligen...

0 Steven Van Vaerenbergh, et al. ∙

∙ 03/28/2019

On the Stability and Generalization of Learning with Kernel Activation Functions

In this brief we investigate the generalization properties of a recently...

0 Michele Cirillo, et al. ∙

∙ 02/06/2019

Widely Linear Kernels for Complex-Valued Kernel Activation Functions

Complex-valued neural networks (CVNNs) have been shown to be powerful no...

0 Simone Scardapane, et al. ∙

∙ 07/11/2018

Recurrent Neural Networks with Flexible Gates using Kernel Activation Functions

Gated recurrent neural networks have achieved remarkable results in the ...

0 Simone Scardapane, et al. ∙

∙ 02/26/2018

Improving Graph Convolutional Networks with Non-Parametric Activation Functions

Graph neural networks (GNNs) are a class of neural networks that allow t...

0 Simone Scardapane, et al. ∙

∙ 02/22/2018

Complex-valued Neural Networks with Non-parametric Activation Functions

Complex-valued neural networks (CVNNs) are a powerful modeling tool for ...

0 Simone Scardapane, et al. ∙

∙ 02/16/2018

Pattern Localization in Time Series through Signal-To-Model Alignment in Latent Space

In this paper, we study the problem of locating a predefined sequence of...

0 Steven Van Vaerenbergh, et al. ∙

∙ 07/13/2017

Kafnets: kernel-based non-parametric activation functions for neural networks

Neural networks are generally built by interleaving (adaptable) linear l...

0 Simone Scardapane, et al. ∙

∙ 06/12/2017

Recursive Multikernel Filters Exploiting Nonlinear Temporal Structure

In kernel methods, temporal information on the data is commonly included...

0 Steven Van Vaerenbergh, et al. ∙

∙ 09/11/2016

On the Relationship between Online Gaussian Process Regression and Kernel Least Mean Squares Algorithms

We study the relationship between online Gaussian process (GP) regressio...

0 Steven Van Vaerenbergh, et al. ∙

∙ 01/27/2015

A Probabilistic Least-Mean-Squares Filter

We introduce a probabilistic approach to the LMS filter. By means of an ...

0 Jesus Fernandez-Bes, et al. ∙

∙ 03/12/2013

Gaussian Processes for Nonlinear Signal Processing

Gaussian processes (GPs) are versatile tools that have been successfully...

0 Fernando Perez-Cruz, et al. ∙

∙ 08/16/2011

Overlapping Mixtures of Gaussian Processes for the Data Association Problem

In this work we introduce a mixture of GPs to address the data associati...

0 Miguel Lázaro-Gredilla, et al. ∙

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