Felipe A. Tobar

Orcid: 0000-0003-2486-3583

According to our database1, Felipe A. Tobar authored at least 46 papers between 2011 and 2023.

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

Timeline

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Bibliography

2023
Computationally-efficient initialisation of GPs: The generalised variogram method.
Trans. Mach. Learn. Res., 2023

Asynchronous Graph Generators.
CoRR, 2023

Gaussian process deconvolution.
CoRR, 2023

Greedy Online Change Point Detection.
Proceedings of the 33rd IEEE International Workshop on Machine Learning for Signal Processing, 2023

2022
On machine learning and the replacement of human labour: anti-Cartesianism versus Babbage's path.
AI Soc., 2022

Modeling Neonatal EEG Using Multi-Output Gaussian Processes.
IEEE Access, 2022

On the Interplay between Information Loss and Operation Loss in Representations for Classification.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Bayesian Reconstruction of Fourier Pairs.
IEEE Trans. Signal Process., 2021

The Wasserstein-Fourier Distance for Stationary Time Series.
IEEE Trans. Signal Process., 2021

Data Science for Engineers: A Teaching Ecosystem.
IEEE Signal Process. Mag., 2021

MOGPTK: The multi-output Gaussian process toolkit.
Neurocomputing, 2021

Studying the Interplay between Information Loss and Operation Loss in Representations for Classification.
CoRR, 2021

Late reverberation suppression using U-nets.
CoRR, 2021

Streaming computation of optimal weak transport barycenters.
CoRR, 2021

A novel notion of barycenter for probability distributions based on optimal weak mass transport.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Detection of blue whale vocalisations using a temporal-domain convolutional neural network.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2021

Bayesian autoregressive spectral estimation.
Proceedings of the IEEE Latin American Conference on Computational Intelligence, 2021

2020
Predicting nationwide obesity from food sales using machine learning.
Health Informatics J., 2020

Gaussian Process Imputation of Multiple Financial Series.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

2019
Compositionally-warped Gaussian processes.
Neural Networks, 2019

Band-Limited Gaussian Processes: The Sinc Kernel.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Low-pass Filtering as Bayesian Inference.
Proceedings of the IEEE International Conference on Acoustics, 2019

2018
Robust Detection of Extreme Events Using Twitter: Worldwide Earthquake Monitoring.
IEEE Trans. Multim., 2018

Improving battery voltage prediction in an electric bicycle using altitude measurements and kernel adaptive filters.
Pattern Recognit. Lett., 2018

Echo state network and variational autoencoder for efficient one-class learning on dynamical systems.
J. Intell. Fuzzy Syst., 2018

Bayesian Learning with Wasserstein Barycenters.
CoRR, 2018

Bayesian Nonparametric Spectral Estimation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning non-Gaussian Time Series using the Box-Cox Gaussian Process.
Proceedings of the 2018 International Joint Conference on Neural Networks, 2018

2017
Recovering Latent Signals From a Mixture of Measurements Using a Gaussian Process Prior.
IEEE Signal Process. Lett., 2017

Spectral Mixture Kernels for Multi-Output Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Improving sparsity in kernel adaptive filters using a unit-norm dictionary.
Proceedings of the 22nd International Conference on Digital Signal Processing, 2017

Initialising kernel adaptive filters via probabilistic inference.
Proceedings of the 22nd International Conference on Digital Signal Processing, 2017

2016
Modelling time series via automatic learning of basis functions.
Proceedings of the 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), 2016

2015
Unsupervised State-Space Modeling Using Reproducing Kernels.
IEEE Trans. Signal Process., 2015

Design of Positive-Definite Quaternion Kernels.
IEEE Signal Process. Lett., 2015

Learning Stationary Time Series using Gaussian Processes with Nonparametric Kernels.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Modelling of complex signals using gaussian processes.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

The widely linear quaternion recursive total least squares.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

2014
Multikernel Least Mean Square Algorithm.
IEEE Trans. Neural Networks Learn. Syst., 2014

Quaternion Reproducing Kernel Hilbert Spaces: Existence and Uniqueness Conditions.
IEEE Trans. Inf. Theory, 2014

A particle filtering based kernel HMM predictor.
Proceedings of the IEEE International Conference on Acoustics, 2014

Estimation of financial indices volatility using a model with time-varying parameters.
Proceedings of the IEEE Conference on Computational Intelligence for Financial Engineering & Economics, 2014

2013
The quaternion kernel least squares.
Proceedings of the IEEE International Conference on Acoustics, 2013

2012
A novel augmented complex valued kernel LMS.
Proceedings of the IEEE 7th Sensor Array and Multichannel Signal Processing Workshop, 2012

2011
Anomaly detection in power generation plants using similarity-based modeling and multivariate analysis.
Proceedings of the American Control Conference, 2011


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