6 citations · 9 across the 5 of their papers we have counts for
5 papers
Modelling calibration uncertainty in networks of environmental sensors
Michael Thomas Smith, Magnus Ross, Joel Ssematimba +4
Networks of low-cost sensors are becoming ubiquitous, but often suffer from poor accuracies and drift. Regular colocation with reference sensors allows recalibration but is complic…
Sparse Gaussian Process Audio Source Separation Using Spectrum Priors in the Time-Domain
Pablo A. Alvarado, Mauricio A. Álvarez, Dan Stowell
Gaussian process (GP) audio source separation is a time-domain approach that circumvents the inherent phase approximation issue of spectrogram based methods. Furthermore, through i…
Efficient Learning of Harmonic Priors for Pitch Detection in Polyphonic Music
Pablo A. Alvarado, Dan Stowell
Automatic music transcription (AMT) aims to infer a latent symbolic representation of a piece of music (piano-roll), given a corresponding observed audio recording. Transcribing po…
A Three Spatial Dimension Wave Latent Force Model for Describing Excitation Sources and Electric Potentials Produced by Deep Brain Stimulation
Pablo A. Alvarado, Mauricio A. Álvarez, Álvaro A. Orozco
Deep brain stimulation (DBS) is a surgical treatment for Parkinson's Disease. Static models based on quasi-static approximation are common approaches for DBS modeling. While this s…
Gaussian Processes for Music Audio Modelling and Content Analysis
Pablo A. Alvarado, Dan Stowell
Real music signals are highly variable, yet they have strong statistical structure. Prior information about the underlying physical mechanisms by which sounds are generated and rul…