Opening Workshop: August 28 – September 1, 2017


This workshop was held at the Penn Pavilion (Level 2), Duke University, Durham, NC.

The Opening Workshop marks the official start of the 2017-18 SAMSI Program on Quasi-Monte Carlo and High-Dimensional Sampling Methods for Applied Mathematics. The first workshop day consists of tutorials that introduce QMC methods, followed by a poster reception. The remaining days feature research presentations, discussion panels, and the formation of (virtual) research working groups.


Tutorial Presentations

Research Talks

Planning for this event is ongoing. Updates will be posted to this page as they transpire.

Schedule and Supporting Media

Printable Schedule
Speaker Abstracts
Participant List
Poster Titles

Monday, August 28, 2017
Penn Pavilion, West Campus, Duke University
** To view the Tutorials for August 28th CLICK HERE

Description Speaker Slides Videos
Introductions and Welcome Ilse Ipsen, Associate Director, SAMSI
Tutorial: Introduction to Quasi-Monte Carlo Art Owen, Stanford University
Tutorial: Lattice Rules for Quasi-Monte Carlo Pierre L’Ecuyer, University of Montreal (CAN)
Tutorial: Error Analysis for Quasi-Monte Carlo Methods Fred Hickernell, Illinois Institute of Technology
Working Groups at SAMSI Ilse Ipsen, Associate Director, SAMSI
Tutorial: Application of QMC to PDEs with Random Coefficients — a survey of analysis and implementation Frances Kuo, UNSW-Sydney (AUS)
Tutorial: Introduction to Global Sensitivity Clémentine Prieur, Grenoble Alpes University (FRA)
Poster Session and Reception

Tuesday, August 29, 2017
Penn Pavilion, West Campus, Duke University

Description Speaker Slides Videos
Bayesian Probabilistic Numerical Methods (Part I) Chris Oates, Newcastle University (ENG)
Bayesian Probabilistic Numerical Methods (Part II) Tim Sullivan, Free University of Berlin / Zuse Institute Berlin (GER)
New Problems and Algorithms at the Interface of Optimal Transport, Statistics and Operations Research Jose Blanchet, Stanford University
Measuring Sample Quality with Stein’s Method Lester Mackey, Microsoft Research
High Accuracy Algorithms for Interpolating and Integrating Multivariate Functions Defined by Sparse Samples in High Dimensions James (Mac) Hyman, Tulane University
Support Points – a new way to compact distributions Simon Mak, Georgia Institute of Technology

Wednesday, August 30, 2017
Penn Pavilion, West Campus, Duke University

Description Speaker Slides Videos
Sequential Function Approximation in High Dimensions with Big Data Dongbin Xiu, Ohio State University
Sparse Polynomial Approximation via Compressed Sensing of High Dimension Functions Clayton Webster, Oak Ridge National Laboratory
Probabilistic Numerical Methods for High-Dimensional Partial Integral Differential Equations Guannan Zhang, Oak Ridge National Laboratory
∞-Variate Integration Grzegorz Wasilkovski, University of Kentucky
Quasi-polynomial Tractability of Linear Tensor Products using Function Values Henryk Wozniakovski, Columbia University
Introduction to Sequential quasi-Monte Carlo Mathieu Gerber, University of Bristol

Thursday, August 31, 2017
Penn Pavilion, West Campus, Duke University

Description Speaker Slides Videos
Deterministic Sampling for Bayesian Computation Roshan Vengazhiyil, Georgia Institute of Technology
Numerical Integration in Hermite Spaces Peter Kritzer, Austrian Academy of Sciences (AUSTRIA)
Lower Bounds for the Discrepancy of Point Sets and Sequences Florian Puchhammer, University of Montreal (CAN)
Higher-Order Convergence for Integration on R Dirk Nuyens, KU Leuven (BEL)
A Sign-definite Heterogeneous Media Wave Propagation Model Mahadevan Ganesh, Colorado School of Mines

Friday, September 1, 2017
Penn Pavilion, West Campus, Duke University

Description Speaker Slides Videos
Multilevel QMC for Forward and Inverse UQ Christoph Schwab, SAM, ETH Zurich (CH)
QMC and Thinning for Empirical Datasets Mike Giles, Oxford University
Generating Random Fields the Circulant Way Ian Sloan, UNSW-Sydney (AUS)
Wrap Up and How to Proceed from Here Ilse Ipsen, Associate Director, SAMSI

Questions: email