# Advanced Monte Carlo Methods for Complex Inference Problems

Created: | 2014-04-25 12:48 |
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Institution: | Isaac Newton Institute for Mathematical Sciences |

Description: | In recent years there has been an explosion of complex data-sets in areas as diverse as Bioinformatics, Ecology, Epidemiology, Finance and Population genetics. In a wide variety of these applications, the stochastic models devised to realistically represent the data generating processes are very high dimensional and the only computationally feasible and accurate way to perform statistical inference is with Monte Carlo.
The focus of this programme is on recent innovations in the field of Monte Carlo methods for inference in complex and intractable statistical problems. This programme will bring together researchers from a broad base, for the first time since 2009, to promote discussion and development of this important and rapidly advancing cross-disciplinary area. It will leverage on the two very successful past programmes which were the INI Programme on Stochastic Computation in the Biological Sciences (23 October - 15 December 2006) and the SAMSI programme on Sequential Monte Carlo (SMC) Methods (September 2008 to August 2009), by taking up the following research threads that have genuinely enthused the wider community of research and applied statisticians over the past couple of years: Approximate Bayesian Computation; SMC and Markov Chain Monte Carlo and their integration; and recent theoretical advancements underpinning these areas. This programme will also hold a workshop in the first week covering the two major themes of this proposal to launch the 4-week programme. The workshop will serve as a catalyst for the remaining 3 weeks of intensive research and aims to cover the following specific areas: ABC: new applications, methodology and theory SMC/MCMC for high dimensional computation The workshop will also have an introductory element to it, aimed at acquainting postgraduate students and postdoctoral researchers with the subject area. Details to follow soon. |

# Media items

This collection contains 38 media items.

### Media items

#### A nested particle filter for online Bayesian parameter estimation in state-space systems

Miguez, J (Universidad Carlos III de Madrid)

Wednesday 30 April 2014, 11:30-12:30

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Wed 7 May 2014

#### ABC methods for Bayesian model choice

Marin, J-M (Université Montpellier 2)

Wednesday 23 April 2014, 09:15-10:15

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 25 Apr 2014

#### Acyclic Monte Carlo: where sequential Monte Carlo meets renormalisation

Kominiarczuk, J (University of Bristol)

Thursday 15 May 2014, 13:30-14:30

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 16 May 2014

#### Adaptive delayed-acceptance pseudo-marginal random walk Metropolis

Sherlock, C (Lancaster University)

Wednesday 23 April 2014, 14:55-15:30

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Approximate Bayesian Inference for Stochastic Processes

Stumpf, M (Imperial College London)

Friday 25 April 2014, 09:50-10:25

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Tue 29 Apr 2014

#### Bayesian inference for sparsely observed diffusions

Golightly, A (Newcastle University)

Thursday 24 April 2014, 11:05-11:40

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Bayesian Uncertainty Quantification for Differential Equations

Girolami, M (University of Warwick)

Tuesday 13 May 2014, 10:00-11:00

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 16 May 2014

#### Consistency and CLTs for stochastic gradient Langevin dynamics based on subsampled data

Vollmer, S (University of Oxford)

Thursday 24 April 2014, 15:50-16:25

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 25 Apr 2014

#### Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator

Pitt, M (University of Warwick)

Tuesday 22 April 2014, 13:45-14:20

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 25 Apr 2014

#### Establishing some order amongst exact approximation MCMCs

Vihola, MS (University of Jyväskylä)

Wednesday 23 April 2014, 11:05-11:40

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Exact approximations

Andrieu, C (University of Bristol)

Tuesday 22 April 2014, 09:15-10:15

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Tue 29 Apr 2014

#### Generalised Particle Filters with Gaussian Mixtures

Li, K (Uppsala University)

Friday 25 April 2014, 11:50-12:25

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Tue 29 Apr 2014

#### Identifiability conditions for partially-observed Markov chains

Douc, R (Telecom SudParis)

Wednesday 23 April 2014, 15:50-16:25

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 25 Apr 2014

#### Lazy ABC

Prangle, D (University of Reading)

Thursday 24 April 2014, 14:20-14:55

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Fri 25 Apr 2014

#### Locally adaptive Monte Carlo methods

Lee, A (University of Warwick)

Tuesday 22 April 2014, 15:50-16:25

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### On the uniform ergodicity of the particle Gibbs sampler

Moulines, E (Télécom ParisTech)

Tuesday 22 April 2014, 11:05-11:40

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Optimal filtering and the dual process

Papaspiliopoulos, O (Institució Catalana de Recerca i Estudis Avançats (ICREA))

Thursday 24 April 2014, 16:25-17:00

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Parallel Markov Chain Monte Carlo

Schmidler, S (Duke University)

Thursday 24 April 2014, 14:55-15:30

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Particle filtering subject to interaction constraints

Whiteley, NP (University of Bristol)

Tuesday 22 April 2014, 16:25-17:00

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014

#### Particle filters and curse of dimensionality

Rebeschini, P (Princeton University)

Thursday 24 April 2014, 11:40-12:15

**Collection**:
Advanced Monte Carlo Methods for Complex Inference Problems

**Institution**:
Isaac Newton Institute for Mathematical Sciences

**Created**:
Mon 28 Apr 2014