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PHYSTAT Seminar: A general introduction to continuous optimization / Mueller, Christian (speaker) (C)
In this talk, I will give an introduction to the field of continuous optimization. I will provide instances of optimization problems that appear in biology and physics through the concept of optimization landscapes. [...]
2019 - 4069. EP-IT Data science seminars External link: Event details In : PHYSTAT Seminar: A general introduction to continuous optimization

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(79)

Classical Splitting of Parametrized Quantum Circuits / Tüysüz, Cenk (speaker) (CQTA, DESY and Humboldt University of Berlin)
In this talk we will dive into the topic of barren plateaus and investigate a new method to avoid them. Barren plateaus appear to be a major obstacle for using variational quantum algorithms to simulate large-scale quantum systems or to replace traditional machine learning algorithms [...]
2023 - 2809. QTI Lectures External link: Event details In : Classical Splitting of Parametrized Quantum Circuits

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(65)

Deciphering jet quenching with JEWEL / Zapp, Korinna Christine (speaker) (LIP Laboratorio de Instrumentacao e Fisica Experimental de Part)
In heavy ion collisions jets arising from the fragmentation of hard quarks and gluons experience strong modifications due to final state re-scattering. This so-called jet quenching is related to the emergence of collectivity and equilibration in QCD [...]
2018 - 3303. Theory Colloquium External link: Event details In : Deciphering jet quenching with JEWEL

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(62)

CMS Invited Talk - "I'm the least sexist person..." - Why It is misleading and dangerous to believe that you are free of prejudice / Degner, Juliane (speaker) (Universität Hamburg)
In this talk, I will give a short introduction into social-cognitive research that investigates the underlying psychological processes of stereotyping, prejudiced evaluation and discriminatory behavior. Specifically, I will focus on automatic and impulsive responses that cause biases in social perception and judgement and explain how they impact our behavior. This event is open to the entire CERN community..
2019 - 4272. Diversity Office External link: Event details In : CMS Invited Talk - "I'm the least sexist person..." - Why It is misleading and dangerous to believe that you are free of prejudice

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(50)

Higher spin JT gravity and a matrix model dual / Kruthoff, Jorrit (speaker) (Stanford)
In this talk I will propose and discuss a generalization of the Saad-Shenker-Stanford duality between matrix models and JT gravity to the case in which the bulk includes higher spin fields. Using an PSL(N,R) BF theory we compute the disk and generalization of the trumpet partition function in this theory [...]
2022 - 4648. TH String Theory Seminar External link: Event details In : Higher spin JT gravity and a matrix model dual

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(46)

PHYSTAT Seminar: Accelerating Bayesian Computation: Parallelizing Markov Chain Monte Carlo / Caldwell, Allen (speaker) (Max-Planck-Institut fur Physik (DE))
A full-fledged Bayesian computation requries evaluation of the posterior probability density in the complete parameter space. This can become very time consuming using commonly used algorithms such as Markov Chain Monte Carlos [...]
2020 - 4063. EP-IT Data science seminars External link: Event details In : PHYSTAT Seminar: Accelerating Bayesian Computation: Parallelizing Markov Chain Monte Carlo

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(46)

PHYSTAT seminar: From COVID-19 Testing to Election Prediction: How Small Are Our Big Data? / Meng, Xiao-Li (speaker) (Harvard University)
The term “Big Data” emphasizes data quantity, not quality. What will be the effective sample size when we take into account the deterioration of data quality because of, for example, the selection bias in COVID-19 testing or the non-response bias in 2016 US Election polling results? This talk provides an answer to such questions, based on the concept of data defect index (ddi) developed in [1]. It will also discuss briefly the application of ddi for 2020 US Election, as reported in [2]. [1] Xiao-Li Meng (2018) “Statistical paradises and paradoxes in big data (I): Law of large populations, big data paradox, and the 2016 US presidential election”, Annals of Applied Statistics 12 685. [2] M [...]
2021 - 4531. EP-IT Data science seminars External link: Event details In : PHYSTAT seminar: From COVID-19 Testing to Election Prediction: How Small Are Our Big Data?

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(44)

An introduction to decomposition / Sharpe, Eric (speaker) (Virginia Tech)
In this talk I will review work on 'decomposition,' a property of 2d theories with 1-form symmetries and, more generally, d-dim'l theories with (d-1)-form symmetries. Decomposition is the observation that such quantum field theories are equivalent to ('decompose into’) disjoint unions of other QFTs, known in this context as "universes.” Examples include two-dimensional gauge theories and orbifolds with matter invariant under a subgroup of the gauge group [...]
2022 - 4283. TH String Theory Seminar External link: Event details In : An introduction to decomposition

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(43)

Indico CONFERENCE: Define the Call for Abstracts / Manzoni, Alex Marc (speaker) ; Ferreira, Pedro (author) (CERN)
In this tutorial, you will learn how to define and open a call for abstracts. When defining a call for abstracts, you will be able to define settings related to the type of questions asked during a review of an abstract, select the users who will review the abstracts, decide when to open the call for abstracts, and more..
2017 - 584. e-learning External link: Event details In : Indico CONFERENCE: Define the Call for Abstracts

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PHYSTAT seminar: On relating Uncertainties in Machine Learning and HEP / Kagan, Michael (speaker) (SLAC National Accelerator Laboratory (US))
Understanding uncertainties is at the core of data analysis in High Energy Collider Physics. As Machine Learning is rapidly becoming used across the collider physics data analysis pipeline, the High Energy Physics (HEP) community must understand when and what kinds of uncertainties are needed on the predictions of these ML models. [...]
2022 - 4284. EP-IT Data Science Seminars External link: Event details In : PHYSTAT seminar: On relating Uncertainties in Machine Learning and HEP

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