Publications de Rafael Eduardo Carrillo Rangel

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Colin Neil Jones, Paul Scharnhorst, Rafael Eduardo Carrillo Rangel, Pierre-Jean Alet, Baptiste Schubnel

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution of a single building. Being fully data-driven, the battery model identificat ...

IEEE2023

Interpretable temporal-spatial graph attention network for multi-site PV power forecasting

Pascal Frossard, Rafael Eduardo Carrillo Rangel, Pierre-Jean Alet, Baptiste Schubnel, Jelena Simeunovic

Accurate forecasting of photovoltaic (PV) and wind production is crucial for the integration of more renewable energy sources into the power grid. To address the limited resolution and costs of methods based on numerical weather predictions (NWP), we take ...

ELSEVIER SCI LTD2022

A real-time optimal inverse planning for Gamma Knife radiosurgery by convex optimization: description of the system and first dosimetry data

Jean-Philippe Thiran, Rafael Eduardo Carrillo Rangel, Rémi Charrier

OBJECTIVE The authors developed a new, real-time interactive inverse planning approach, based on a fully convex framework, to be used for Gamma Knife radiosurgery. ...

AMER ASSOC NEUROLOGICAL SURGEONS2018

A Fourier dimensionality reduction model for big data interferometric imaging

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

Data dimensionality reduction in radio interferometry can provide savings of computational resources for image reconstruction through reduced memory footprints and lighter computations per iteration, which is important for the scalability of imaging method ...

Oxford Univ Press2017

Fourier dimensionality reduction of radio-interferometric data

Jean-Philippe Thiran, Yves Wiaux, Rafael Eduardo Carrillo Rangel, Vijay Kartik

Next-generation radio-interferometers face a computing challenge with respect to the imaging techniques that can be applied in the big data setting in which they are designed. Dimensionality reduction can thus provide essential savings of computing resourc ...

2017

Ultrafast ultrasound imaging as an inverse problem: Matrix-free sparse image reconstruction

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Adrien Georges Jean Besson, Rafael Eduardo Carrillo Rangel, Florian Martinez, Marcel Arditi

Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution of the image reconstruction problem. An alternative to DAS consists in using iterative techniques which require both an a ...

2017

A compressed-sensing approach for ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Rafael Eduardo Carrillo Rangel, Marcel Arditi, Adrien Georges Jean Besson

Ultrasonography uses multiple piezo-electric element probes to image tissues. Current time-domain beamforming techniques require the signal at each transducer-element to be sampled at a rate higher than the Nyquist criterion, resulting in an extensive amou ...

2017

Robust sparse image reconstruction of radio interferometric observations with PURIFY

Yves Wiaux, Rafael Eduardo Carrillo Rangel, Jason Douglas McEwen

Next-generation radio interferometers, such as the Square Kilometre Array (SKA), will revolutionise our understanding of the universe through their unprecedented sensitivity and resolution. However, to realise these goals significant challenges in image an ...

OUP2016

A compressed beamforming framework for ultrafast ultrasound imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Rafael Eduardo Carrillo Rangel, Marcel Arditi, Adrien Georges Jean Besson, Olivier Bernard

Classical beamforming methods, based on Delay- And-Sum (DAS) require an extensive number of samples and delay calculations to obtain high-quality images. Compressed Beamforming (CB) proposes an alternative to DAS, based on compressed sensing, which aims at ...

Ieee2016

Morphological component analysis for sparse regularization in plane wave imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Eric Bezzam, Rafael Eduardo Carrillo Rangel, Marcel Arditi, Adrien Georges Jean Besson

Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-p ...

Ieee2016