Week 23.01.2022 – 29.01.2022

We read the book on Quantum Field Theory in Curved Spacetime and Black Hole Thermodynamics by Robert M. Wald.

This is an online club held every Thursday 4:15pm-5:15pm on teams. Contact: george.papadopoulos@kcl.ac.uk

We are delighted to invite you to a talk by Isao Makabe as part of the series of careers talks ‘on the transition from academia to industry’ by former PhD students in the Department of Mathematics.

Isao is a data scientist at Permutive, an ad-tech startup, which builds an audience platform built on edge computing for advertisers and publishers while keeping everyone's data safe. He has been working as a data scientist for over three years in BtoB companies building big data and machine learning solutions. Before that, he studied theoretical physics PhD at KCL as an international student under the supervision of Gerard Watts, graduating in 2017.

While this event is primarily intended as a careers event for PhD students, all mathematics students are welcome to attend. The talk will take place on Microsoft Teams, please join via the below at the time of the event. There is no need to register.

https://teams.microsoft.com/l/meetup-join/19%3ameeting_M2U2NzkwYTItMGUwOS00MzNjLTgxNDMtMWQ0OTY3Y2I0YmJj%40thread.v2/0?context=%7b%22Tid%22%3a%228370cf14-16f3-4c16-b83c-724071654356%22%2c%22Oid%22%3a%22d0ab862e-769f-41f8-ac51-282fb61fd3c4%22%7d

This event is part of a series of Maths Careers Talks: PhD Stories of The Transition from Academia to Industry, organised by Professor Tiziana Di Matteo.

Factor copula models have been recently proposed for describing the joint distribution of a large number of variables in terms of a few common latent factors. A Bayesian procedure is employed in order to make fast inferences for multi-factor and structured factor copulas. To deal with the high dimensional structure, a Variational Inference (VI) algorithm is applied to estimate different specifications of factor copula models. Compared to the Markov Chain Monte Carlo (MCMC) approach, the variational approximation is much faster and could handle a sizeable problem in limited time. Another issue of factor copula models is that the bivariate copula functions connecting the variables are unknown in high dimensions. An automatic procedure is derived to recover the hidden dependence structure. By taking advantage of the posterior modes of the latent variables, the bivariate copula functions are selected by minimizing the Bayesian Information Criterion (BIC). Simulation studies in different contexts show that the procedure of bivariate copula selection could be very accurate in comparison to the true generated copula model. The proposed procedure is illustrated with two high dimensional real data sets.

Speaker (12:05-12:30): Rosa Winter

Title: Lines and rational points on del Pezzo Surfaces

------------------------------
Speaker (12:30-12:55): Aled Walker

Title: Poissonian gap distributions of dilated sequences


------------------------------

The event is also streamed online via the Teams meeting link below:

https://teams.microsoft.com/l/meetup-join/19%3ameeting_OGY4OTIzNWYtNGU2NS00MGJhLWEzZmUtYzRiNzJkNDgyNGUx%40thread.v2/0?context=%7b%22Tid%22%3a%228370cf14-16f3-4c16-b83c-724071654356%22%2c%22Oid%22%3a%22f5e6659a-9991-4207-82e6-e0a00414c096%22%7d

15:15: Intro
15:30: Damian Galante: De sitter space and holography
16:00: Eugene Lim: Can Inflation inflate
16:30: Break
16:45: Nadav Drukker: Circular knitting and the framing anomaly
17:15: Malcolm Fairbairn: Post LHC Dark Matter hunting
18:00: Pub, to be determined.

Talks will be presented live in the Nash Auditorium, K2.31 and streamed on Teams