COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |

University of Cambridge > Talks.cam > Signal Processing and Communications Lab Seminars > Multilevel sequential Monte Carlo Samplers.

## Multilevel sequential Monte Carlo Samplers.Add to your list(s) Download to your calendar using vCal - Dr Ajay Jasra, National University of Singapore
- Thursday 28 May 2015, 15:00-16:00
- LR5, Department of Engineering.
If you have a question about this talk, please contact Prof. Ramji Venkataramanan. In this talk we consider the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h_L. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. It is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context. This is a joint work with Alex Beskos (UCL), Kody Law (KAUST), Raul Tempone (KAUST) and Yan Zhou (NUS).
This talk is part of the Signal Processing and Communications Lab Seminars series. ## This talk is included in these lists:- All Talks (aka the CURE list)
- Cambridge Centre for Data-Driven Discovery (C2D3)
- Cambridge University Engineering Department Talks
- Cambridge talks
- Centre for Smart Infrastructure & Construction
- Chris Davis' list
- Featured lists
- Information Engineering Division seminar list
- Interested Talks
- LR5, Department of Engineering
- School of Technology
- Signal Processing and Communications Lab Seminars
- Trust & Technology Initiative - interesting events
- bld31
- ndk22's list
- ob366-ai4er
- rp587
Note that ex-directory lists are not shown. |
## Other listsThe Leverhulme Centre for Human Evolutionary Studies Seminars IoA Stellar Pops Type the title of a new list here Cambridge Public Policy Lecture Series Cambridge Energy Conference Confronting History, the Archive and the 'Stranger' in Educational Research## Other talksBrest-Litovsk and the Making of Modern Ukraine and Russia CANCELLED DUE TO STRIKE ACTION Recent advances in understanding climate, glacier and river dynamics in high mountain Asia Making Smart Decisions in Systems Design: How to Engineer Decisions in a Connected World? A compositional approach to scalable statistical modelling and computation A physical model for wheezing in lungs |