Speaker: Hadis Anahideh, Research Assistant Professor of Mechanical and Industrial Engineering, UIC Description: limited informative data remains the primary challenge for the optimization expensive...
Speaker: Jiuhai Chen, Ph.D. candidate (AMAT) 91×ÔÅÄ Description: In this work, we present a new particle-based VI methods for Bayesian inference, inspired by a discrete energetic variational...
Speaker: Jagadeeswaran Rathinavel, 91×ÔÅÄ Ph.D. candidate (AMAT) Description: Automatic cubatures approximate integrals to user-specified error tolerances. For high dimensional problems, it is...
Speaker: Romà Domènech Masana, 91×ÔÅÄ Ph.D. candidate (AMAT) Description: The idea focuses on making more complex splits. A Random Tree is grown by several steps. A Random Tree needs a dataset...
Speaker: Kan Zhang, 91×ÔÅÄ Ph.D. candidate (AMAT) Description: Computing the expected value of a parameter via Bayesian inference involves the numerical approximation of the quotient of two...
Host Department of Applied Mathematics Speaker Yiou Li Department of Mathematical Sciences, Depaul University https://csh.depaul.edu/faculty-staff/faculty-a-z/Pages/mathematical-sciences/yiou-li.aspx...
Host Department of Applied Mathematics Speaker Lulu Kang Department of Applied Mathematics, Illinois Institute of Technology http://math.iit.edu/~lkang2/ Description Gaussian process regression is a...
Host Department of Applied Mathematics Speaker Fred Hickernell Department of Applied Mathematics, Illinois Institute of Technology Description Function approximation is relatively simple compared to...
Host Department of Applied Mathematics Speaker Jiuhai Chen Department of Applied Mathematics, Illinois Institute of Technology www.iit.edu/applied-math/about/phd-students Description PDE and ODE are...
Host Department of Applied Mathematics Speaker Stephen Wiggins School of Mathematics, University of Bristol http://www.bristol.ac.uk/maths/people/stephen-r-wiggins/index.html Description The...
