Guang Lin
Purdue University
3:45 PM
127 Hayes-Healy Center
A tea will precede the event at 3:15 pm in 101A Crowley Hall.
Towards Third Wave AI: Interpretable, Robust Trustworthy Machine Learning for Diverse Applications in Science and Engineering
This talk aims to close the gap by developing new theories and scalable numerical algorithms for complex dynamical systems that can be realistically predicted and validated. We are creating new technologies that can be translated into more secure and reliable new trustworthy AI systems that can be deployed for real-time complex dynamical system prediction, surveillance, and applications to improve the stability and efficiency of complex dynamical systems. We will introduce new Neural Networks that learn functionals and nonlinear operators from functions with simultaneous uncertainty estimates.
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