=========================================================== TENTH INTERNATIONAL WORKSHOP MESHFREE METHODS FOR PARTIAL DIFFERENTIAL EQUATIONS =========================================================== > PLEASE REMEMBER: Abstract submission deadline is approaching! You can still send your abstract till June 13! DATE: September 2-4, 2019 LOCATION: Bonn, Germany SPONSORS: Sonderforschungsbereich 1060 (http://sfb1060.iam.uni-bonn.de/) Hausdorff Center for Mathematics (http://www.hcm.uni-bonn.de/) ORGANIZERS: Ivo Babuska (University of Texas at Austin, USA) Jiun-Shyan Chen (University of California, San Diego, USA) Wing Kam Liu (Northwestern University, USA) Cheng-Tang Wu (Livermore Software Technology Corporation, USA) Harry Yserentant (Technische Universitaet Berlin, Germany) Michael Griebel (Rheinische Friedrich-Wilhelms-Universitaet Bonn, Germany) Marc Alexander Schweitzer (Rheinische Friedrich-Wilhelms-Universitaet Bonn, Germany) CONTACT: https://ins.uni-bonn.de/group/schweitzer/page/meshfree-2019 meshfree@ins.uni-bonn.de DEADLINE AND IMPORTANT DATES: June 13, 2019 Abstract submission deadline June 21, 2019 Sending out letters of acceptance TRAVEL: INFORMATION ON TRAVEL AND HOTELS: https://archive.ins.uni-bonn.de/schweitzer.ins.uni-bonn.de/meshfree/travel-i... SOME WORKSHOP LOCATIONS: https://drive.google.com/open?id=1pbNg-E3mFzo1KTl3mbv37fM2acM&usp=sharing The numerical treatment of partial differential equations with meshfree discretization techniques has been a very active research area in recent years. While the fundamental theory of meshfree methods has been developed and considerable advances of the various methods have been made, many challenges in the mathematical analysis and practical implementation of meshfree methods remain. Moreover, meshfree and particle methods are natural candidates to tackle problems in data science due to their mathematical background in scattered data approximation and statistical mechanics. The efficient treatment of large sets of high-dimensional data by machine learning techniques such as kernel-based approaches is a major challenge and an important aspect in many application areas ranging from engineering, material science, chemistry to the life sciences. Meshfree methods, particle methods, kernel approaches and generalized finite element methods have undergone substantial development since the mid 1990s. The growing interest in these methods is in part due to the fact that they are quite flexible numerical tools and can be interpreted in various different of ways. For instance, meshfree methods can be viewed as a natural extension of classical finite element and finite difference methods to scattered node configurations with no fixed connectivity. Moreover, meshfree methods have some advantageous features which are especially attractive when dealing with multiscale phenomena: A-priori knowledge about the particular local behavior of the solution can be introduced easily in the meshfree approximation space, and an enrichment of a coarse scale approximation with fine scale information is possible in a seamless fashion. The implementation of meshfree methods and their parallelization however requires special attention, for instance with respect to numerical integration. Finally, kernel-based approaches can be interpreted as collocation and sampling processes giving rise to the natural connection of meshfree methods to data analysis methods and machine learning. This symposium aims to promote collaboration among engineers, mathematicians, and computer scientists and industrial researchers to address the development, mathematical analysis, and application of meshfree and particle methods especially to multiscale phenomena. It continues the 2-year-cycled Workshops on Meshfree Methods for Partial Differential Equations. While contributions in all aspects of meshfree methods are invited, some of the key topics to be featured are - Mathematical theory of meshfree, generalized finite element, and particle methods - Application of meshfree, generalized/extended finite element methods e.g. to * multiscale problems * multiphysics problems * non-local models * problems with multiple discontinuities and singularities - Problems in high-dimensions - Kernel-based scattered data techniques for data analysis and machine learning - Data-driven material models - Identification and characterization of problems where meshfree methods have clear advantage over classical approaches The three day workshop program will consist of invited lectures and contributed papers. The workshop will be held at the University Club of the University of Bonn in downtown Bonn. ---------------------------------------------------- International Workshop Meshfree Methods Institut fuer Numerische Simulation Rheinische Friedrich-Wilhelms Universitaet Bonn Endenicher Allee 19b D-53115 Bonn URL: http://wissrech.ins.uni-bonn.de/meshfree Mail: meshfree@ins.uni-bonn.de