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<div>Dear Cedar,</div>
<div> Can you please post this announcement? Thanks. </div>
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We would like to invite contributions to session “Machine learning and statistical inference techniques” at the Thirteenth European Space Weather Week (ESWW) November, 2016, Belgium. The session abstract can be found below. The deadline for abstract submission
is June 6, 2016. More information about the meeting and venue can be found at ESWW website: <a href="http://www.stce.be/esww13/program/sessions.php" style="color: purple;">http://www.stce.be/esww13/program/sessions.php</a>. <o:p></o:p></p>
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Enrico Camporeale (<a href="mailto:e.camporeale@cwi.nl" style="color: purple;">e.camporeale@cwi.nl</a>), Simon Wing, Jay Johnson, and Jacob Bortnik<o:p></o:p></p>
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_______________________________________________________________________________________________<o:p></o:p></p>
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<b><span style="font-size: 18pt; font-family: Arial; color: rgb(55, 112, 181); text-transform: uppercase;">SESSION - MACHINE LEARNING AND STATISTICAL INFERENCE TECHNIQUES<o:p></o:p></span></b></p>
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<b><span style="font-size: 10pt; font-family: Arial; color: rgb(64, 64, 64);">Enrico Camporeale (CWI, The Netherlands); Simon Wing (JHUAPL, USA); Jay Johnson (PPPL, USA); Jacob Bortnik (UCLA, USA)</span></b><span style="font-size: 10pt; font-family: Arial; color: rgb(64, 64, 64);"><br>
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<span style="font-size: 10pt; font-family: Arial; color: rgb(64, 64, 64);">The science of 'making predictions' has been historically based on statistical inference and, more recently, on machine learning techniques. Other areas that are concerned with predictions
and are somehow overlapping in scope and methodology include system identification, data assimilation, information theory, signal processing, and uncertainty quantification. All of these disciplines have been studied and developed in context typically unrelated
to Space Weather. However, the science behind Space Weather is becoming increasingly multidisciplinary, and the ease of accessing and processing large volumes of data makes these techniques very attractive for the Space Weather community. This session is devoted
to contributions that use any of these approaches for Space Weather forecasting.<o:p></o:p></span></p>
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<div>-- </div>
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Simon Wing<br>
240-228-8075 (Voice)<br>
<a href="simon.wing@jhuapl.edu">simon.wing@jhuapl.edu</a></span></font><span style="font-size:14pt"><font face="Calibri,Verdana,Helvetica,Arial"><br>
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