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SUMMARY:Bayes@Lund 2019
DTSTART;VALUE=DATE-TIME:20190507T063000Z
DTEND;VALUE=DATE-TIME:20190507T150000Z
DTSTAMP;VALUE=DATE-TIME:20191120T222352Z
UID:indico-event-1191@indico.esss.lu.se
DESCRIPTION:Thank you all who participated in Bayes@Lund 2019 and who made
it such a successful and enjoyable event! :)\n\nAll best\,\nThe Organizer
s\nRasmus Bååth\, Alex Holmes\, and Ullrika Sahlin\n\nBelow you will fi
nd the original webpage of Bayes@Lund 2019.\n\n\nYou are welcome to partic
ipate in the sixth edition of Bayes@Lund!\n\nThe purpose of this conferenc
e is to bring together researchers and professionals working with or inter
ested in Bayesian methods. Bayes@Lund aims at being accessible to resear
chers with little experience of Bayesian methods while still being releva
nt to experienced practitioners. The focus is on how Bayesian methods are
used in research and in the industry\, what advantages Bayesian methods h
ave over classical alternatives\, and how the use and teaching of Bayesian
methods can be encouraged. (see last year's conference for what to expec
t).\n\nThe conference will take place at Lund University\, Sweden on the
7th of May 2019 starting at 9.00 and ending at 17.00. It will include cont
ributed talks and invited presentations. Please register for the conferenc
e here.\n\nThe Program\n\nThe program is now finalized! For a list of all
the speakers\, and abstracts for all talks\, do check out the book of abs
tracts:\n\n \n\nSlides and info\n\nSome
of the speakers have agreed on sharing slides and information regarding th
eir presentations which you'll find here:\n\n\n Visualisation for refining
and communicating Bayesian analyses -- Robert Grant\n \n More info about
Robert's book Data Visualization: charts\, maps and interactive graphics
: http://robertgrantstats.co.uk/dataviz-book\n \n \n Extending Bayes to M
ake Optimal Decisions -- Jonas Kristoffer Lindeløv\n \n Slides: https:/
/github.com/bayesat/bayesat.github.io/blob/master/lund2019/slides/jonas_li
ndelov_bayes_at_lund_2019.pdf\n Notebook with code and explanation (highl
y reccomended!): https://lindeloev.github.io/utility-theory/\n \n \n Sign
al detection theory as bridge for Bayesian statistics and modelling -- Ge
rit Pfuhl\n \n Slides: https://github.com/bayesat/bayesat.github.io/blob
/master/lund2019/slides/gerit_pfuhl_bayes_at_lund_2019.pdf\n \n \n Rich-ma
n's Monte Carlo: Uncertainty Analysis in Excel -- Dmytro Perepolkin\n \n
Code: https://github.com/dmi3kno/PMMC_BayesAtLund19 \n Slides: http://
bit.ly/PMMC_BayesAtLund19\n \n \n Bayesian vs. Frequentism for experimenta
lists -- Jakob Lavröd\n \n Slides: https://github.com/bayesat/bayesat.g
ithub.io/raw/master/lund2019/slides/jakob_lavrod_bayes_at_lund_2019.pptx\n
\n \n Bayesian Deep Learning Applications in Biomedicine -- Nikolay Oskol
kov\n \n Slides: https://github.com/bayesat/bayesat.github.io/blob/maste
r/lund2019/slides/nikolay_oskolkov_bayes_at_lund_2019.ppt\n \n \n Bayesian
inference of conformational ensembles from small-angle scattering data --
Wojciech Potrzebowski\n \n Slides: https://github.com/bayesat/bayesat.g
ithub.io/blob/master/lund2019/slides/wojciech_potrzebowski_bayes_at_lund_2
019.pptx\n \n \n Automatic Learning of Summary Statistics for Approximate
Bayesian Computation Using Deep Learning -- Samuel Wiqvist\n \n Slides:
https://github.com/bayesat/bayesat.github.io/blob/master/lund2019/slides/s
amuel_wiqvist_bayes_at_lund_2019.pdf\n \n \n What cause successful learnin
g in Bayesian methods? -- George Moroz\n \n Slides: https://github.com/b
ayesat/bayesat.github.io/blob/master/lund2019/slides/george_moroz_19.05.07
_Lund_Bayes.pdf\n \n \n\n\n \n\n\n\nInvited Speaker: Maggie Lieu\n\nMaggi
e is an astrophysics research fellow working at the European Space Agency
in Madrid. Her main research involves modelling the mass distribution of c
lusters of galaxies to understand the nature of dark matter and dark energ
y in our Universe. Maggie's talk is Hierarchical models and their applica
tions in astronomy\; how hierarchical models can be a powerful tool for i
nference.\n\n \n\nInvited Speaker: Robert Grant\n\nRobert Grant is a medi
cal statistician\, turned freelance trainer\, coach and writer in Bayesia
n models and data visualisation. His book Data Visualisation: charts maps
and interactive graphics is published by CRC Press. His talk Visualisa
tion for refining and communicating Bayesian analyses will review relevan
t general principles of effective visualisation\, recent work on Bayesian
workflow\, and the role of interactive graphics.\n\nPre-conference Bayesi
an tutorial\n\nAre you interested in Bayesian statistics and want to get u
p to speed? Then join the pre-conference Bayesian tutorial. This 3h tutor
ial will be given by Rasmus Bååth and will go through the fundamentals o
f Bayesian statistics using R. It will be based on the online course of th
e same name and requires no prior knowledge of Bayesian statistics but bas
ic knowledge of the R programming language.\n\nThe tutorial is free of cha
rge and takes place on the 6th of May 14.00 - 17.00 at Lund University\, S
weden. Please register here.\n\n\n\nhttps://indico.esss.lu.se/event/1191/
LOCATION:Palaestra\, Lund University\, Sweden
URL:https://indico.esss.lu.se/event/1191/
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