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EURA NOVA selected for the erasmus mundus joint doctorate (EMJD) in distributed computing

The EMJD in Distributed Computing (EMJD-DC) is an international joint doctoral school for the study of distributed computing. EMJD-DC combines a well-structured, interdisciplinary training programme with high-quality research work. The training and research is carried out in cooperation with leading research groups from four universities in different countries: UPC (Spain), KTH (Sweden), IST Lisbon (Portugal), and UCL (Belgium).

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Calibrate to Interpret

Trustworthy machine learning is driving a large number of the ML community works in order to improve ML acceptance and adoption. In this paper, we show a first link between uncertainty and explainability, by studying the relation between calibration and interpretation.
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Mass Estimation of Planck Galaxy Clusters using Deep Learning

Galaxy cluster masses can be inferred indirectly using measurements from X-ray band, Sunyaev-Zeldovich (SZ) effect signal or optical observations. Unfortunately, all of them are affected by some bias. Alternatively, we provide an independent estimation of the cluster masses from the Planck PSZ2 catalogue of galaxy clusters using a machine-learning method.
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