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Upcoming Events

Tomasz R. Bielecki - Department of Applied Mathematics, Illinois Institute of Technology
Apr 23, 2019 - 11:25am to 12:45pm
Department of Applied Mathematics - Seminar - Rettaliata Engineering Center, Room 103
TBA
Tue.
Apr 23
Frederi Viens - Department of Statistics and Probability, Michigan State University
Apr 29, 2019 - 1:50pm to 2:55pm
Department of Applied Mathematics - Colloquia - Rettaliata Engineering Center, Room 104
TBA
Mon.
Apr 29
Sergey Nadtochiy - Department of Applied Mathematics, Illinois Institute of Technology
Apr 30, 2019 - 11:25am to 12:45pm
Department of Applied Mathematics - Seminar - Rettaliata Engineering Center, Room 103
TBA
Tue.
Apr 30

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Event Archive

Guang Lin - Department of Mathematics, Department of Statistics & School of Mechanical Engineering, Purdue University
Feb 1, 2019 - 2:30pm to 3:30pm
Center for Interdisciplinary Scientific Computation (CISC) - Seminar - Rettaliata Engineering Center, Room 103
Experience suggests that uncertainties often play an important role in quantifying the performance of complex systems. Therefore, uncertainty needs to be treated as a core element in the modeling, simulation, and optimization of complex systems. The field of uncertainty quantification (UQ) has... read more
Fri.
2/1/19
Matthew Dixon - Department of Applied Mathematics, Illinois Institute of Technology
Jan 29, 2019 - 11:25am to 12:45pm
Department of Applied Mathematics - Seminar - Rettaliata Engineering Center, Room 103
Modeling counterparty risk is computationally challenging because it requires the simultaneous evaluation of all the trades with each counterparty under both market and credit risk. We present a multi-Gaussian process regression approach, which is well suited for OTC derivative portfolio valuation... read more
Tue.
1/29/19
David Bindel - Department of Computer Science, Cornell University
Jan 28, 2019 - 1:50pm to 2:55pm
Department of Applied Mathematics - Colloquia - Rettaliata Engineering Center, Room 104
Gaussian processes (GPs) define a distribution over functions that generalizes the multivariate normal distribution over vector spaces. Long used as a tool for spatio-temporal statistical modeling, GPs are also a key part of the modern arsenal in machine learning. Unfortunately, Gaussian process... read more
Mon.
1/28/19

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