BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Europe/Stockholm
X-LIC-LOCATION:Europe/Stockholm
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=-1SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=-1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20210916T132529Z
LOCATION:Lise Girardin
DTSTART;TZID=Europe/Stockholm:20210708T170000
DTEND;TZID=Europe/Stockholm:20210708T190000
UID:submissions.pasc-conference.org_PASC21_sess166@linklings.com
SUMMARY:Applied Cutting-Edge Machine Learning in Cosmology and Particle Ph
 ysics
DESCRIPTION:Minisymposium\n\nCosmology and particle physics both strive to
  gain a deeper understanding of the history, the composition and the inner
  workings of the Universe. While complementary in many aspects, cosmology 
 and particle physics also share many things: they try to find answers to t
 he same open questions, they use similar detectors and analysis techniques
 , and they both have marvelously precise models. Both disciplines rely hea
 vily on Monte Carlo simulation techniques, they have ever-increasing datas
 ets with planned next-generation experiments, which face yet-unsolved comp
 uting challenges related to triggering, data reconstruction and simulation
 , as well as data storage. Traditional computing approaches are not scalin
 g to these New Challenges and are limiting the physics output. New Computi
 ng Paradigms are needed to make progress. Recent developments in machine l
 earning techniques coupled with custom hardware may offer potential direct
 ions of improvement. The symposium will highlight several prominent areas 
 in this fast emerging and thriving field with a diverse set of elect inter
 national speakers from research Universities both in physics and computer 
 science, research institutes and industry. This rich diversity will provid
 e different angles from which to shine light on the problem for maximum cl
 arity and accessibility of the underlying challenges and the proposed meth
 ods to address them.\n\nSimulation-Based Inference for Precision Measureme
 nts\n\nCranmer\n\nParticle physicisits have developed high-fidelity s
 imulators, which include computational manifestations of our fundamen
 tal theories as well as detailed models for how our complex particle 
 detectors will respond. Ironically, while these simulators provide our hig
 hest-fidelity physical...\n\n---------------------\nGradient-Based Methods
  for Black-Box Tuning and Optimisation\n\nUstyuzhanin\n\nTuning simulation
  tools and finding optimal device configurations is a challenging task tha
 t usually implies expertise and significant computational investments. Wel
 l-known methods such as evolution algorithms or Bayesian optimisation help
  to address those challenges. However, those approaches rely ...\n\n------
 ---------------\nLearning the Universe with Machines\n\nHo\n\nI will brief
 ly talk about all the modern challenges in model testing in astrophysics a
 nd how machine learning can help. In particular, I will touch on the appli
 cation and development of using symbolic regression combined with deep lea
 rning architecture to advance our understanding of the Universe.&n...\n\n-
 --------------------\nHow Can Physics Inform the Design of Intelligence?\n
 \nToth, Rezende, Jaegle, Racaniere, Botev...\n\nBiological intelligence di
 d not evolve in a vacuum - its design and function are constrained and gui
 ded by the core structures of our universe. In this talk I will present a 
 hypothesis that in order to build artificial intelligence, it is also impo
 rtant to consider the fundamentals of our world stru...\n\n\nDomain: CS an
 d Math, Emerging Applications, Physics, Engineering
END:VEVENT
END:VCALENDAR