A preliminary version of the book of abstracts is available at -V1.pdf.

It includes all informations but will be updated before the conference



Belown we provide  a general idea of the provisional program.

Sunday, July, 1: tutorials

14h-15h30: Alexander Keller

15h30-16h: coffee break

16h-17h30: Gerardo Rubino

Monday, July, 2

8h20-8h30: Opening

8h30-9h30: Plenary talk, Christophe Andrieu

9h30-10h: Coffee break

10h-12h: Parallel sessions

12h-13h45: Lunch break (on your own)

13h45-14h45: Plenary talk, Christoph Schwab

14h45-15h45: Parallel sessions

15h45-16h15: Coffee break

16h15-17h45: Parallel sessions

18h30: Welcome reception (City Hall)

Tuesday, July, 3

8h30-9h30: Plenary talk, Barry Nelson

9h30-10h: Coffee break

10h-12h: Parallel sessions

12h-13h45: Lunch break (on your own)

13h45-14h45: Plenary talk, Pierre Henry Labordère

14h45-15h45: Parallel sessions

15h45-16h15: Coffee break

16h15-17h45: Parallel sessions

18h30: Wine & Cheese (location: Bar L’Aventure)

Wednesday, July, 4

8h30-9h30: Plenary talk, Eric Moulines

9h30-10h: Coffee break

10h-12h: Parallel sessions

12h-13h45: Lunch break (on your own)

13h45-15h45: Parallel sessions

16h: Guided visit of Rennes

19h: Banquet at “Chateau d’Apigné

Thursday, July, 5

8h25-8h30: Journal of Computing Young Researcher Award 2018

8h30-9h30: Plenary talk, Friedrich Pillichshammer 

9h30-10h: Coffee break

10h-12h: Parallel sessions

12h-13h45: Lunch break (on your own)

13h45-14h45: Plenary talk, Clémentine Prieur

14h45-15h45: Parallel sessions

15h45-16h15: Coffee break

16h15-17h45: Parallel sessions


Friday, July, 6

8h30-9h30: Plenary talk, Marvin Nakayama

9h30-10h: Coffee break

10h-12h: Parallel sessions

12h-13h45: Lunch break (on your own)

13h45-15h15: Parallel sessions

15h15:  Goodbye coffee


Sessions Description:

Numerical approximation of SDEs under non-standard assumptions (1)

      • Larisa Yaroslavtseva: On loss of regularity in the initial value for SDEs with non-globally Lipschitz continuous coefficients
      • Diyora Salimova: Numerical approximations of nonlinear stochastic  differential equations
      • Michaela Szölgyenyi: Euler-type schemes for SDEs with discontinuous drift
      • Holger Stroot: Strong Approximation of Stochastic Mechanical Systems with Nonlinear Holonomic Constraints

Numerical approximation of SDEs under non-standard assumptions (2)

      • Mario Hefter: Lower Error Bounds for Strong Approximation of Scalar SDEs with non-Lipschitzian Coefficients
      • Mike Giles: Multilevel Monte Carlo Method for Ergodic SDEs without Contractivity
      • Dai Taguchi: Semi-implicit Euler-Maruyama scheme for non-colliding particle systems
      • Sotirios Sabanis: MCMC algorithms based on numerical approximations of SDEs with locally Lipschitz coefficients

Non-Reversible Markov Chain Monte Carlo (1)

      • Joris Bierkens: Reflections on the bouncy particle sampler and Zig-Zag sampler

      • Alex Thiery: Discrete-Time Bouncy Particle Samplers and Generalisations
      • Alain Durmus: On the convergence of Hamiltonian Monte Carlo
      • Arnak Dalalyan: User-friendly guarantees for the Langevin Monte Carlo

Non-Reversible Markov Chain Monte Carlo (2)

      • Christian Robert: Generalized Bouncy Particle Sampler
      • Pierre Monmarché: Geometric ergodicity for the Bouncy Particle Sampler
      • Chris Sherlock: Explicit, non-reversible, contour-hugging MCMC moves
      • Michela Ottobre: Sampling and irreversibility

Construction of QMC point sets and sequences

      • Frances Kuo: Discrete least squares approximation on multivariate polynomial spaces using lattice points
      • Kosuke Suzuki: Lattice Rules in Non-periodic Subspaces of Sobolev Spaces
      • Ralph Kritzinger: Haar Analysis of Digital Nets and Sequences
      • Dirk Nuyens: Lattice rules with random number of points and near $O(n^{-\alpha-1/2})$ convergence

QMC and applications

      • Ian Sloan: On the generation of random fields
      • Roswitha Hofer: Kronecker–Halton sequences in ${\mathbb F}_p((X^{-1}))$
      • Mario Neumueller: Asymptotic Behaviour of the Sudler Product of Sines for Quadratic Irrationals

Stochastic Computation and Complexity (1)

      • Thomas Mueller-Gronbach: On sub-polynomial lower error bounds for strong approximation of SDEs
      • Andreas Roessler: Algorithms for the Approximation of Iterated Stochastic Integrals in Infinite Dimensions
      • Timo Welti: Deep optimal stopping: Solving high-dimensional optimal stopping problems with deep learning
      • Monika Eisenmann: A Randomized Time-Stepping Method for Differential Equations with Time-Irregular Coefficients

Stochastic Computation and Complexity (2)

      • Steffen Dereich: Central limit theorems for multilevel stochastic approximation algorithms
      • Raphael Kruse: On two quadrature rules for stochastic integrals with fractional Sobolev regularity
      • Sonja Cox: Stochastic integration in quasi-Banach spaces: what Besov regularity does the stochastic heat equation posess?
      • Mihaly Kovacz: Weak and strong approximation of fractional order elliptic equations with spatial white noise

Stochastic Computation and Complexity (3)

      • Alvin Tse: Multilevel Monte Carlo for McKean-Vlasov SDEs
      • Martin Redmann: Solving parabolic rough partial differential equations using regression
      • Yue Wu: Randomized Numerical Schemes for SDE/SPDEs
      • Stefan Heinrich: Lower bounds for stochastic integration in fractional Sobolev classes

Forward and inverse UQ with hierarchical models (1)

      • Benjamin Peherstorfer: Multifidelity Monte Carlo estimation with adaptive low-fidelity  models
      • Ahmed Kebaier: Adaptive Importance Sampling for Multilevel Monte Carlo Euler method
      • Sebastian Krumsheid: Multilevel Monte Carlo Approximation of Functions
      • Abdul-Lateef Haji-Ali: Multilevel Nested Simulation for Efficient Risk Estimation

Forward and inverse UQ with hierarchical models (2)

      • Jonas Latz: Multilevel Sequential${}^2$ Monte Carlo for Bayesian Inverse Problems
      • Hakon Hoel: Multilevel ensemble Kalman filtering for spatio-temporal processes
      • Joakim Beck: Hierarchical sampling methods for Bayesian experimental design
      • Kody Law: Inference using Multilevel Monte Carlo

Forward and inverse UQ with hierarchical models (3)

      • Matteo Croci: Efficient white noise sampling and coupling for multilevel Monte Carlo
      • Lukas Mayer: Multilevel Monte Carlo for the Quadrature of SDEs Based on Random Bits
      • Soeren Wolfers: Multilevel weighted least squares polynomial approximation
      • Andreas Stein: An adaptive Multilevel Monte Carlo algorithm for advection-diffusion PDEs with random discontinuous coefficients

New applications of QMC in physics, energy and environment (1)

      • Werner Roemisch: Randomized QMC methods for two-stage stochastic optimization problems: Recent progress
      • Hernan Leovey: Tensor Products, Classical Weighted Sobolev Spaces, Quasi-Monte Carlo and Energy Management

New applications of QMC in physics, energy and environment (2)

      • Karl Jansen: Lattice Field Theory: a physics case for high dimensional integration
      • Julia Volmer: Improving Monte Carlo integration by symmetrization

Points on the Sphere and Other Manifolds: New Frontiers and Recent Progress (1)

      • Johann Brauchart: Overview/Hyperuniformity in the Compact Setting: Deterministic and Random Aspects
      • Jordi Marzo: Determinantal Point Processes and Optimality

Points on the Sphere and Other Manifolds: New Frontiers and Recent Progress (2)

      • Damir Ferizovic: Bounds for the Green Energy on SO(3)
      • Maria De Ujue Etayo: t-Designs on Manifolds: an Asymptotic Bound on the Number of Points

Points on the Sphere and Other Manifolds: New Frontiers and Recent Progress (3)

      • Peter D. Dragnev: Universal Bounds on Energy of Codes and Designs in Various Settings
      • Tetiana Stepaniuk: Estimates for numerical integration errors on unit spheres of arbitrary dimension

Practice of QMC methods (1)

      • Adrian Ebert:     Efficient usage and construction of QMC methods
      • Michael_Gnewuch: Probabilistic discrepancy bounds for Latin hypercube sampling with and without padding

Practice of QMC methods (2)

      • Yuya Suzuki: Rank-1 lattices and higher-order exponential splitting for the multi-dimensional time-dependent Schrodinger equation
      • Ana I. Gomez: Generation of True Random Numbers using quasi-Monte Carlo Methods

Acceleration of MCMC

      • Thomas Catanach: Sequential Tempered Markov Chain Monte Carlo for Bayesian Inference
      • Maksym Byshkin: Fast Maximum Likelihood estimation via Equilibrium Expectation for large network data

Multilevel Monte Carlo methods

      • Emil Løvbak: Multilevel Monte Carlo for Asymptotic-Preserving Particle Schemes
      • Andreas Van Barel: Robust Optimization of PDE Constrained Systems


      • Arnaud Lionnet: The Numerical Approximation Of Polynomial-Growth Backward Stochastic Differential Equations
      • Marie BILLAUD FRIESS: Stochastic methods for solving partial differential equations in high dimension

Rare event simulation

      • Pierre Nyquist: Rare-event simulation in machine learning: Infinite swapping and restricted Boltzmann machines
      • Art Owen: ALOE importance sampler for the union of rare events
      • Chang-Han Rhee: Efficient Rare-Event Simulation for Multiple Jump Events in Regularly Varying Random Walks and Compound Poisson Processes

Simulation in finance and operation management

      • Lihua Sun: A Nonprametric Method for Pricing and Hedging American Options
      • Jun Luo: Speeding Up Ranking and Selection Procedures for Large Scale Problems Using Cloud Computing
      • Guangxin Jiang: Constructing Surface for Derivative Pricing and Sensitivity Analysis

Markov Chain QMC

      • Shin Harase : An Implementation of Short-Period Tausworthe Generators for Markov Chain quasi-Monte Carlo Method
      • Tobias Schwedes: Adaptive Importance Sampling for Markov Chain Quasi-Monte Carlo
      • Rami El Haddad: Sudoku Sampling For Markov Chains Simulation

MCMC and large size

      • Paulo Orenstein: Scalable MCMC for Bayes Shrinkage Priors
      • James Johndrow: Scaling MCMC to Large Problem Sizes

Algorithms for High-Dimensional Approximation (and Integration) Problems

      • Yuhan Ding: An Optimal Automatic Algorithm Employing Continuous Linear Functionals
      • Aicke Hinrichs: How good is random information? – Approximation in the Hilbert space setting
      • Klaus Ritter: Integration and $L_2$-Approximation on Hermite Spaces of Functions of Infinitely-Many Variables
      • Henryk Wozniakowski: Tractability of Multivariate Approximation over Weighted Standard Sobolev Spaces

Uncertainty Quantification and Sensitivity Analysis in Computational Finance

      • Sergei Kucherenko: Application of QMC and Global Sensitivity Analysis to Option Pricing and Greeks
      • Emanouil Atanassov: Sensitivity Analysis of Quasi-Monte Carlo methods for the Heston Model
      • Giray Okten: Sensitivity and Robustness of Financial Models
      • Alexender Kreinin: Sensitivities of Exotic Portfolios

MC in Finance

      • Daniel Roth: Monte Carlo pathwise sensitivities for barrier options
      • Warren Volk-Makarewicz: Detecting the Presence of Jumps in Option Prices

Design and testing of random number generators

      • Sebastiano Vigna: xoshiro/xoroshiro: new families of high-quality, high-speed PRNGs
      • Hiroshi Haramoto: Testing the Reliability of Statistical Tests for Pseudorandom Number Generators
      • Pierre L’Ecuyer: On the Lattice Structure of MIXMAX Random Number Generators

Computational challenges in finance

      • Christian Bayer: Smoothing the payoff for computation of basket options
      • Jean-François Chassagneux: Cubature method to solve BSDEs: error expansion and complexity control
      • Gilles Pagès: The Parareal Algorithm for American Options

Rare events

      • Jere Koskela: Sequential Monte Carlo for efficient sampling of rare trajectories in reverse time
      • Harsha Honnappa: Large Deviations of Gaussian Block Extrema
      • Ad Ridder: Monte Carlo Methods for Insurance Risk Computation

Approximating Markov chain Monte Carlo

      • Krzysztof Latuszynski: Barkerâ??s algorithm for Bayesian inference with intractable likelihoods
      • Blazej Miasojedow: On a new approach of the Unadjusted Langevin Algorithm via convex optimization
      • Nikolaus Schweizer: Approximation of geometrically ergodic Metropolis-Hastings algorithms
      • Matti Vihola: Importance Sampling Type Estimators based on Approximate Marginal MCMC

Importance Splitting for Rare Event Simulation

      • Charles-Edouard Brehier: New results concerning Adaptive Multilevel Splitting algorithms
      • Gregoire Ferre: Numerical analysis and long time stability of Feynman-Kac dynamics
      • Nicolas Champagnat: Convergence of Fleming-Viot particle systems to the mininal quasi-stationary distribution
      • Henri Louvin: Application of an importance splitting method to radiation shielding simulations

Dispersion and Applications

      • Mario Ullrich: The inverse of the dispersion depends logarithmically on the dimension
      • David Krieg: On the Dispersion of Sparse Grids
      • Daniel Rudolf: Recovery algorithms for high-dimensional rank one tensors
      • Jan Vybiral: On further aspects of dispersion

When to stop a simulation

      • Fred Hickernell: Fast Adaptive Bayesian Cubature Using Low Discrepancy Sampling
      • Robert Kunsch: Solvable Integration Problems and Optimal Sample Size Selection
      • Mark Huber: Improved Light Tailed Sample Averages for Robust Estimation of the Mean

Recent advances in particle filtering

      • Mathieu Gerber: Interacting Particles for Online Inference on Static Parameters Using Streaming Data
      • Anna Wigren: Improving the particle filter in high dimensions using conjugate artificial process noise
      • Pierre Del Moral: On the stability and the uniform propagation of chaos properties of ensemble Kalman–Bucy filters
      • Nicolas Chopin: Convergence of resampling algorithms

Nuclear applications

      • Bert Mortier: Study of Source Term Estimators in Coupled Finite-Volume/Monte-Carlo Methods for Plasma Edge Simulations in Nuclear Fusion
      • Dmitry Savin: Monte Carlo simulation of multiple particle spectra with energy and momentum conservation
      • Zhicheng Ji: A Batch on Patch Parallel Scheme in Monte Carlo Particle Transport Program
      • Gang Li: High Precision Shielding Calculation For Qinshan-I Reactor Model With Monte Carlo Particle Transport Code JMC

Non-uniform Random Variate Generation (1)

      • Josef Leydold: Optimal Importance Sampling Density 1: Approximation Methods
      • Wolfgang Hormann: Optimal Importance Sampling Density 2: Evaluating CDF and PDF of the Sum of Lognormals
      • Luca Martino: Parsimonious Adaptive Rejection Sampling Schemes
      • Efraim Shmerling: Acceptance Tail Sampling Method

Non-uniform Random Variate Generation (2)

      • Moran Peri: A Table Method for Sampling from Multivariate Distrbutions with Unbounded Support
      • Yael Hagbi: Generation of Waiting Time in a Markovian Trial Sequence

Low discrepancy sequences and point sets – devoted to the 80th birthday of Henri Faure (1)

      • Christiane Lemieux: Counting Points in Boxes with Henri Faure: From Discrepancy Bounds to Dependence Structures
      • Peter Kritzer: Discrepancy Bounds for Nets and Sequences
      • Takashi Goda: Quasi-Monte Carlo integration over a triangle
      • Florian Pausinger: On the intriguing search for good permutations

Low discrepancy sequences and point sets – devoted to the 80th birthday of Henri Faure (2)

      • Gerhard Larcher: On discrepancy and pair correlation of sequences in the unit interval
      • Josef Dick: Richardson Extrapolation of Polynomial Lattice Rules

Simulation of mean-field stochastic differential equations

      • Mireille Bossy: Particle algorithm for McKean SDE: rate of convergence  for some non-smooth drift interaction  kernel
      • Denis Belomestny: Variance reduction for mean-field stochastic differential equations
      • Lukasz Szpruch: Weak error expansion for mean-field SDEs
      • Alexandre Zhou: Numerical Analysis of a Particle Calibration Procedure for Local and Stochastic Volatility Models

Analysis of low-discrepancy sequences

      • Lisa Kaltenböck: On Bounded Remainder Sets for Sequences $(\{a_n\alpha\})_{n\geq 1}$ with $(a_n)_{n \geq 1}$ a Lacunary Integer Sequence
      • Hiroki Kajiura: Characterization of Matrices B such that (I,B,B^2) Generates a Digital Net with t-value Zero
      • Raffaelo Seri : The Asymptotic Distribution of Riesz’ Energy

Jittered sampling

      • Benjamin Doerr: A Sharp Discrepancy Bound for Jittered Sampling
      • Matasake Hirao: On p-frame potential of random point configurations on the sphere

Improving MC and QMC integration

      • Florian Puchhammer: Density estimation by randomized quasi-Monte Carlo
      • Yuji Nakatsukasa: Variance reduction in Monte Carlo integration via function approximation

Variance reduction/estimator efficiency/rare-event probability

      • Nadhir Ben Rached: Variance Reduction Techniques for the Accurate Computation of the Distribution of the sum of Ordered Random Variables
      • Guo-Jhen Wu: Infinite swapping using iid samples
      • Thomas Taimre: Exploiting Asymptotics and Polar Coordinates for Rare Tail Estimation
      • Fan Zhang: Data-Driven Distributionally Robust Optimization via Optimal Transport: Algorithms and Applications

Efficient Sampling

      • Benjamin Jourdain: Sampling of probability measures in the convex order and approximation of Martingale Optimal Transport problems
      • Daniele Bigoni: Adaptive Construction of Transport Maps for Efficient Sampling
      • Andrés F. López-Lopera: Efficiently approximating Gaussian Process Emulators with Inequality Constraints using MC/MCMC

Stochastic Differential Equations

      • Przemyslaw Zielinski: Micro-macro acceleration method with relative entropy moment matching for scale-separated SDEs
      • Andreas Petersson: Rapid covariance based sampling of finite element approximations of linear SPDE in MLMC

Sequential methods and efficiency

      • Andrea Arnold: Sequential Monte Carlo Methods for Time-Varying Parameter Estimation
      • Chris Drovandi: New Insights into History Matching via Sequential Monte Carlo
      • Victor Elvira: Rethinking the Effective Sample Size in Importance Sampling

Monte Carlo in physics (1)

      • Matthias Baeten: Convergence Analysis of a Coupled Monte-Carlo/Pseudo-Timestepping Scheme Arising in Plasma Edge Simulation
      • DanHua ShangGuan: Efficient Strategy for Global Tallying in the Monte Carlo Criticality Calculation
      • Natalya Tracheva: Monte Carlo method projective estimators for angular and temporal characteristics evaluation of polarized radiation

Monte Carlo in physics (2)

      • Anna Korda: Monte-Carlo methods for reconstructing the aerosol scattering matrix
      • Mariya Korotchenko: Some Applications of Dynamics Simulation for Multi-Particle Systems in the Kinetic Model Framework

o MCQMC in Computer Graphics

      • Nikolaus Binder: Fragmented Radix Trees for Efficient Sampling of Discrete Probability Distributions
      • Christophe Hery: On the Usage of Control Variates for Monte Carlo Direct Illumination in Movie Rendering
      • Wenzel Jacob: Reversible Jump Metropolis Light Transport using Inverse Mappings

Monte Carlo for rare events

      • Javiera Barrera: Sharp Bounds for the Reliability of a k-out-of-n System Under Dependent Failures Using Cutoff Phenomenon Techniques
      • Gerardo Rubino: The Multi-Level Creation Process in Flow Network Reliability Estimation
      • Hector Cancela: Studying Metabolic Networks Through Monte Carlo Simulations
      • Ajit Rai: Availability Estimation of Markovian Reliability Systems with Logistics via Cross-Entropy

QMC and quadrature strategies for integration

      • Pieterjan Robbe: A Multigrid Multilevel Quasi-Monte Carlo Method with Sample Reuse
      • Lutz Kammerer Combining Multiple Rank-1 Lattice Rules for Approximation
      • Mutsuo Saito: Experimental Comparison of Higher-Order Digital Nets for QMC
      • Matthias Sachs: Quadrature Points via Heat Kernel Repulsion

MCMC : Model selection and convergence

      • Faming Liang: Average (E)BIC-like Criteria for Bayesian Model Selection
      • Georgy Sofronov: Spatial Segmentation via the Generalized Gibbs Sampler
      • Dootika Vats: MCMC for Bayesian penalized regression
      • Marie Vialaret: On the convergence time of some non-reversible Markov chain Monte-Carlo methods

Handling Discontinuities in QMC with Applications to Computational Finance


SDE, solutions and convergence rate

      • Abir Ghannoum : Mean Reflected Stochastic Differential Equations with jumps : Simulation by using Particle System
      • Flavius Guias: High precision solvers for autonomous systems of differential equations based on Markov jump processes
      • Céline Labart : Approximation rate of BSDEs using random walk

Applications of MC

    • Lingbin Bian; Network structure change point detection using randomize-then-optimize
    • Julien Roussel: A Perturbative Approach to Control Variates in Molecular Dynamics
    • Chi-Ok Hwang: Laplace Surface Green’s Function on a Spherical Surface for Last-passage Monte Carlo Methods