22 citations · 44 across the 17 of their papers we have counts for
23 papers
Efficient Interpretable Nonlinear Modeling for Multiple Time Series
Kevin Roy, Luis Miguel Lopez-Ramos, Baltasar Beferull-Lozano
Predictive linear and nonlinear models based on kernel machines or deep neural networks have been used to discover dependencies among time series. This paper proposes an efficient…
Consistent Signal Reconstruction from Streaming Multivariate Time Series
Emilio Ruiz-Moreno, Luis Miguel López-Ramos, Baltasar Beferull-Lozano
Digitalizing real-world analog signals typically involves sampling in time and discretizing in amplitude. Subsequent signal reconstructions inevitably incur an error that depends o…
An Online Multiple Kernel Parallelizable Learning Scheme
Emilio Ruiz-Moreno, Baltasar Beferull-Lozano
The performance of reproducing kernel Hilbert space-based methods is known to be sensitive to the choice of the reproducing kernel. Choosing an adequate reproducing kernel can be c…
A Trainable Approach to Zero-delay Smoothing Spline Interpolation
Emilio Ruiz-Moreno, Luis Miguel López-Ramos, Baltasar Beferull-Lozano
The task of reconstructing smooth signals from streamed data in the form of signal samples arises in various applications. This work addresses such a task subject to a zero-delay r…
Random Feature Approximation for Online Nonlinear Graph Topology Identification
Rohan Money, Joshin Krishnan, Baltasar Beferull-Lozano
Online topology estimation of graph-connected time series is challenging, especially since the causal dependencies in many real-world networks are nonlinear. In this paper, we prop…
Explainable nonlinear modelling of multiple time series with invertible neural networks
Luis Miguel Lopez-Ramos, Kevin Roy, Baltasar Beferull-Lozano
A method for nonlinear topology identification is proposed, based on the assumption that a collection of time series are generated in two steps: i) a vector autoregressive process…