Antônio H. Ribeiro

Orcid: 0000-0003-3632-8529

According to our database1, Antônio H. Ribeiro authored at least 25 papers between 2018 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.



In proceedings 
PhD thesis 




On Merging Feature Engineering and Deep Learning for Diagnosis, Risk Prediction and Age Estimation Based on the 12-Lead ECG.
IEEE Trans. Biomed. Eng., July, 2023

Overparameterized Linear Regression Under Adversarial Attacks.
IEEE Trans. Signal Process., 2023

Invertible Kernel PCA With Random Fourier Features.
IEEE Signal Process. Lett., 2023

End-to-end Risk Prediction of Atrial Fibrillation from the 12-Lead ECG by Deep Neural Networks.
CoRR, 2023

Deep networks for system identification: a Survey.
CoRR, 2023

Regularization properties of adversarially-trained linear regression.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ECG-Based Electrolyte Prediction: Evaluating Regression and Probabilistic Methods.
CoRR, 2022

Surprises in adversarially-trained linear regression.
CoRR, 2022

How Convolutional Neural Networks Deal with Aliasing.
Proceedings of the IEEE International Conference on Acoustics, 2021

First Steps Towards Self-Supervised Pretraining of the 12-Lead ECG.
Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

Beyond Occam's Razor in System Identification: Double-Descent when Modeling Dynamics.
CoRR, 2020

Deep Energy-Based NARX Models.
CoRR, 2020

Contextualized interpretable machine learning for medical diagnosis.
Commun. ACM, 2020

On the smoothness of nonlinear system identification.
Autom., 2020

Explaining End-to-End ECG Automated Diagnosis Using Contextual Features.
Proceedings of the Machine Learning and Knowledge Discovery in Databases. Applied Data Science and Demo Track, 2020

Automatic 12-lead ECG Classification Using a Convolutional Network Ensemble.
Proceedings of the Computing in Cardiology, 2020

Explaining Black-Box Automated Electrocardiogram Classification to Cardiologists.
Proceedings of the Computing in Cardiology, 2020

Beyond exploding and vanishing gradients: analysing RNN training using attractors and smoothness.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

SciPy 1.0-Fundamental Algorithms for Scientific Computing in Python.
CoRR, 2019

The trade-off between long-term memory and smoothness for recurrent networks.
CoRR, 2019

Automatic Diagnosis of the Short-Duration 12-Lead ECG using a Deep Neural Network: the CODE Study.
CoRR, 2019

Deep Convolutional Networks in System Identification.
Proceedings of the 58th IEEE Conference on Decision and Control, 2019

"Parallel Training Considered Harmful?": Comparing series-parallel and parallel feedforward network training.
Neurocomputing, 2018

Automatic Diagnosis of Short-Duration 12-Lead ECG using a Deep Convolutional Network.
CoRR, 2018

Lasso Regularization Paths for NARMAX Models via Coordinate Descent.
Proceedings of the 2018 Annual American Control Conference, 2018