Home

• When? Every Tuesday at 2:30pm
• Where? LG.04, Department of Statistics, 24-29 St Giles'

Upcoming

Date	Topic	Presenters
26 January 2016	External talk - "Extremal point process of the branching Brownian motion"	Julien Berestycki
2 February 2016	W&J chap 3 - 4.1	Leonard Hasenclever + Stefan Webb
9 February 2016	W&J rest of chap 4, (chap 5)	Thibaut Lienart, Xiaoyu Lu
16 February 2016	Leave Pima Indians Alone	Marco, Valerio
23 February 2016	Convergent EP for Dynamic Bayes Nets (Heskes & Zoeter), extended version
1 March 2016	visitor talk	Kamalika Chaudhuri
8 March 2016	Stochastic EP, BB-alpha

SDEs and Stochastic Gradient Sampling

Date	Topic	Presenters
19 April	SDEs	Tigran Nagapetyan Recommended Reading: Chapter 3 of [Omiros notes] (http://www.econ.upf.edu/~omiros/course_notes.pdf) Further Reading Duncan, Computational Stochastic Processes, see repository
26 April	SDEs and their discretisations	Tigran Nagapetyan and Sebastian Vollmer
03 May	Ergodicity of SDEs and their discretisation	Sebastian Vollmer

Upcoming Topics:

Variational inference and expectation propagation (Yee Whye)

• Wainwright & Jordan
• Leave Pima Indians Alone (Ridgeway & Chopin)
• EP for approximate inference (Heskes & Zoeter)
• BB-alpha
• Convergent EP (Lobato),
• Fast convergent algorithms for EP (Seeger, Nickish)
• EP for GP (which paper?)
• Variational inference for Monte Carlo objectives

SDEs and SGMCMC (Sebastian)

• Emily Fox Family of SDEs paper
• Changyou Chen & Lawrence Carin series (Dec 2015)

Bayesian Nonparametrics and stochastic processes

• [Gnedin & Pitman. Notes on the occupancy problem with infinitely many boxes: general asymptotics and power laws. Proba. surveys.]
• Harry Crane on Ewens' Sampling Formula
• Asmussen & Rosinsky, Cohen & Rosinsky on Gaussian tail approximations of Levy processes
• Tree processes (DDT, PYDT, coalescent, Gibbs fragmentation, continuum random trees?)
• Harry Crane on networks
• Neil Sheppard on Levy processes
• GP inducing points
• GP kernel structure learning (Duvenaud et al arxiv:1302.4922v4)
• Structure learning in matrix factorisation (Grosse et al)

Bayesian learning in general

• Bayesian dark Knowledge (Korattikara et al)

External speakers

• Andriy Mnih, Nicholas Heess, Charles Blundell
• Richard Xu

Model checking, evaluation (BDA Gelman)

• Posterior predictive checks
• WAIC

Past Meetings (2014-2015)