An upcoming workshop in June 2017 will explore applications of probabilistic numerics.
June 5 – 9, 2017
the Institute for Computational and Experimental Research in Mathematics at Brown University will host a seminar on Probabilistic Scientific Computing: Statistical inference approaches to numerical analysis and algorithm design. Organized by Philipp Hennig, George Em Karniadakis, Michael A Osborne, Houman Owhadi and Paris Perdikaris, the seminar will feature invited and contributed talks by experts from applied mathematics, statistics and computer science. It will explore the connections between statistical inference and numerical computation, and explore new theory, algorithms and programming paradigms for computation in areas like machine learning, computational statistics and scientific computation.
Interested researchers can apply to participate on the seminar webpage.
[image credit: Wikipedia user Biscotti999. CC BY-SA 3.0]
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems
For website questions and technical problems please contact:
© 2019 Max-Planck-Gesellschaft -