Stochastic numerical algorithms, multiscale modeling and high-dimensional data analytics
(July 18 — 22, 2016)

Picture
A measure induced by a stochastic differential equation whose drift induces a limit cycle, presenting a challenge to local simulation schemes. [Photo credit: Mark Girolami]

Description

This workshop is concerned with sampling challenges, modeling and simulation for data-rich applications in high dimensions. It brings together mathematicians, statisticians and computational scientists to explore the interplay between computational applied mathematics and data science. On the agenda will be novel developments in the study of complex phenomena based on data-analytic techniques, such as efficient calculation of ergodic (long term) averages and statistical inference under a wide range of geometric, physical and analytical constraints.

In applied mathematics and computational science, in particular in molecular modeling, image analysis and geosciences, among others, many objects of interest are high-dimensional and stochastic, and a wide variety of techniques have been developed for sampling and approximating the quantities of interest. Similar issues arise in the area of data science and statistical modeling, where learning problems in the presence of high-dimensional data require efficient computational algorithms for sampling and approximation.

The workshop will focus on recent advances in the design of rigorous discrete-dynamics based sampling approaches, algorithms development for large-scale data analysis and stochastic dynamical systems, scalable and rigorous numerical methods for stochastic differential equations and sampling from high-dimensional distributions, and exploitation of low-dimensional structures in high-dimensional data and stochastic dynamical systems for model reduction and efficient Monte-Carlo schemes. The meeting will foster the interchange and deployment of the latest methodologies for sampling and approximation.


Organizing Committee

  • Mark Girolami
    (Warwick University)
  • Susan Holmes
    (Stanford University)
  • Benedict Leimkuhler
    (University of Edinburgh)
  • Mauro Maggioni
    (Duke University)

= speaker    = poster presenter

Monday July 18, 2016
Time Description Speaker Location Abstracts Slides
8:30 - 8:55Registration11th Floor Collaborative Space
8:55 - 9:00WelcomeICERM Director11th Floor Lecture Hall
9:00 - 9:35Revisiting Monte Carlo EstimationMark Girolami, University of Warwick11th Floor Lecture Hall
9:45 - 10:20Sequential matrix completionSergio Bacallado, Universiy of Cambridge11th Floor Lecture Hall
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10:30 - 11:00Coffee/Tea Break11th Floor Collaborative Space
11:00 - 11:35Fast Robustness Quantification with Variational BayesTamara Broderick, Massachusetts Institute of Technology11th Floor Lecture Hall
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11:45 - 12:20Adaptive sparse quadrature for high-dimensional integration with Gaussian distribution- application to Bayesian inverse problems.Peng Chen, The University of Texas at Austin11th Floor Lecture Hall
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12:30 - 3:00Break for Lunch / Free Time
3:00 - 3:35Data-driven stochastic model reductionFei Lu, University of California, Berkeley11th Floor Lecture Hall
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3:45 - 4:20Mathematics for data-driven modeling - The science of crystal ballsYannis Kevrekides, Princeton University11th Floor Lecture Hall
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4:30 - 6:00Welcome Reception11th Floor Collaborative Space

Tuesday July 19, 2016
Time Description Speaker Location Abstracts Slides
9:00 - 9:35Multi-fidelity information fusion algorithms for high dimensional systems and massive data-setsGeorge Karniadakis, Brown University11th Floor Lecture Hall
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9:45 - 10:20Product form stationary distributions of stochastic reaction networks with non-mass action kinetics, and application to constrained averaging of multiscale systemsSimon Cotter, University of Manchester11th Floor Lecture Hall
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10:30 - 11:00Coffee/Tea Break11th Floor Collaborative Space
11:00 - 11:35Statistical inference of stochastic single-cell and single-molecule dynamicsHeinz Koeppl, Technische Universität Darmstadt11th Floor Lecture Hall
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11:45 - 12:20Measure transport, variational inference, and low-dimensional mapsYoussef Marzouk, Massachusetts Institute of Technology11th Floor Lecture Hall
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12:30 - 2:15Break for Lunch / Free Time
2:15 - 2:50Stochastic integrators for multiscale and ergodic dynamical systemsAssyr Abdulle, École Polytechnique Fédérale de Lausanne11th Floor Lecture Hall
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3:00 - 3:35Stratification for Markov chain Monte Carlo samplingJonathan Weare, University of Chicago11th Floor Lecture Hall
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3:45 - 4:15Coffee/Tea Break11th Floor Collaborative Space
4:15 - 5:00Lightning Talks11th Floor Lecture Hall

Wednesday July 20, 2016
Time Description Speaker Location Abstracts Slides
9:00 - 9:35Efficient methods for estimating stochastic gradients and sensitivity indices in complex stochastic dynamicsMarkos Katsoulakis, University of Massachusetts, Amherst11th Floor Lecture Hall
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9:45 - 10:20Quasi-Reliable Estimates of Effective Sample SizeRobert Skeel, Purdue University11th Floor Lecture Hall
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10:20 - 10:30Group Photo in Lecture Hall11th Floor Lecture Hall
10:30 - 11:00Coffee/Tea Break11th Floor Collaborative Space
11:00 - 11:35Ergodic Stochastic Differential Equations and Sampling- A numerical analysis perspectiveKonstantinos Zygalakis, University of Edinburgh11th Floor Lecture Hall
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11:45 - 1:50Break for Lunch / Free Time
2:00 - 2:35Ensemble preconditioning schemes for Bayesian inverse problemsCharles Matthews, University of Chicago11th Floor Lecture Hall
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2:45 - 3:20Accurate sampling algorithms for constraints and noisy gradientsBenedict Leimkuhler, University of Edinburgh11th Floor Lecture Hall
3:30 - 5:00Poster Session and Coffee/Tea Break11th Floor Collaborative Space

Thursday July 21, 2016
Time Description Speaker Location Abstracts Slides
9:00 - 9:35Variational Hamiltonian Monte CarloBabak Shababa, The Center for Statistical Consulting11th Floor Lecture Hall
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9:45 - 10:20Scalable and Efficient MCMC Algorithms for Complex PosteriorsYian Ma, University of Washington11th Floor Lecture Hall
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10:30 - 11:00Coffee/Tea Break11th Floor Collaborative Space
11:00 - 11:35Sub-Gaussian estimators of the mean of a random matrix with entries possessing only two momentsStanislav Minsker, University of Southern California11th Floor Lecture Hall
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11:45 - 12:20Adaptive two-stage integrators for sampling algorithms based on Hamiltonian dynamicsElena Akhmatskaya, Basque Center for Applied Mathematics - BCAM11th Floor Lecture Hall
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12:30 - 2:15Break for Lunch / Free Time
2:15 - 2:50Scalable Bayesian Inference with Hamiltonian Monte CarloMichael Betancourt, University of Warwick11th Floor Lecture Hall
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3:00 - 3:35Computing ergodic limits for SDEsMichael Tretyakov, The University of Nottingham11th Floor Lecture Hall
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3:45 - 4:15Coffee/Tea Break11th Floor Collaborative Space
4:15 - 5:00Panel Discussion11th Floor Lecture Hall

Friday July 22, 2016
Time Description Speaker Location Abstracts Slides
9:00 - 9:35Geometric Methods for the Approximation of High-dimensional Dynamical SystemsMauro Maggioni, Johns Hopkins University11th Floor Lecture Hall
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9:45 - 10:20Scalable algorithms for Markov process parameter inferenceDarren Wilkinson, Newcastle University11th Floor Lecture Hall
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10:30 - 11:00Coffee/Tea Break11th Floor Collaborative Space
11:00 - 11:35Covariance-controlled adaptive Langevin thermostat for large-scale Bayesian samplingXiaocheng Shang, Brown University11th Floor Lecture Hall
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11:45 - 12:20Irreversible langevin samplers and variance reduction- a large deviations approach and diffusion on graphsKonstantinos Spiliopoulos, Boston University11th Floor Lecture Hall
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12:30 - 2:15Break for Lunch / Free Time
2:15 - 2:50Simple ergodic variants of the Hamiltonian Monte Carlo methodJesus Sanz-Serna, Universidada Carlos III de Madrid11th Floor Lecture Hall
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3:00 - 3:45Wrapup Q&A11th Floor Lecture Hall