[Halld-offline] Fwd: [Eic-news-l] Machine Learning Seminar, November 6

[Mark Ito]

from Markus Diefenthaler et al., should be interesting...



-------- Forwarded Message --------
Subject: 	[Eic-news-l] Machine Learning Seminar, November 6
Date: 	Thu, 1 Nov 2018 17:32:14 -0400
From: 	Markus Diefenthaler <mdiefent at jlab.org>
To: 	eic-news-l at lists.bnl.gov



Hello, everyone:

We would like to invite you to a Machine Learning Seminar at the EIC 
Center at Jefferson Lab (https://www.eiccenter.org 
<https://urldefense.proofpoint.com/v2/url?u=https-3A__www.eiccenter.org_&d=DwMFaQ&c=lz9TcOasaINaaC3U7FbMev2lsutwpI4--09aP8Lu18s&r=JKPm21o4RG5_VIn2fXX6tQ&m=wexFIceK7NwtTZSHtiQN2qLOcTWC3fuU5Y8uMgU8Gvg&s=qx4LFbuyCX4dvOHmwnZ7_g0HM3TiLE61j-KeZIzhjo4&e=>): 


Artificial intelligence (AI) and machine learning (ML) methods will 
allow to accelerate research in NP. On Tuesday, November 6, we will 
review promising R&D areas in ML in HEP and NP. Anima Anandkumar 
(Caltech) will address in her keynote “Opportunities for infusing 
physics and domain knowledge into AI/ML algorithms”. An overview about 
the R&D on scientific machine learning will be provided by Steven Lee 
(DOE ASCR) and Wahid Bhimji (NERSC). A.-K. Burns (William & Mary), C. 
Fanelli (MIT), and A. Tsaris (Fermilab) will present specific use cases 
for ML methods in HEP and NP.

You are highly welcome to join our discussions at Jefferson Lab or via 
BlueJeans (details on https://www.jlab.org/indico/event/247/). Please 
find our poster with the detailed program on:

    https://www.jlab.org/indico/event/247/session/8/material/0/0.pdf


Best regards,

Amber, Chip, Graham, Mark, and Markus.


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