activity
20182021
collaborators

7 papers

eess.IV2021

How Convolutional Neural Networks Deal with Aliasing

Antônio H. Ribeiro, Thomas B. Schön

The convolutional neural network (CNN) remains an essential tool in solving computer vision problems. Standard convolutional architectures consist of stacked layers of operations t…

cs.LG2020

Deep Energy-Based NARX Models

Johannes N. Hendriks, Fredrik K. Gustafsson, Antônio H. Ribeiro +2

This paper is directed towards the problem of learning nonlinear ARX models based on system input--output data. In particular, our interest is in learning a conditional distributio…

cs.LG2020

Beyond Occam's Razor in System Identification: Double-Descent when Modeling Dynamics

Antônio H. Ribeiro, Johannes N. Hendriks, Adrian G. Wills +1

System identification aims to build models of dynamical systems from data. Traditionally, choosing the model requires the designer to balance between two goals of conflicting natur…

eess.SY2019

Deep Convolutional Networks in System Identification

Carl Andersson, Antônio H. Ribeiro, Koen Tiels +2

Recent developments within deep learning are relevant for nonlinear system identification problems. In this paper, we establish connections between the deep learning and the system…

cs.MS2019

SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python

Pauli Virtanen, Ralf Gommers, Travis E. Oliphant +32

SciPy is an open source scientific computing library for the Python programming language. SciPy 1.0 was released in late 2017, about 16 years after the original version 0.1 release…

cs.LG2019

Automatic diagnosis of the 12-lead ECG using a deep neural network

Antônio H. Ribeiro, Manoel Horta Ribeiro, Gabriela M. M. Paixão +9

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacke…