no code implementations • 14 Dec 2023 • Can Cui, Zichong Yang, Yupeng Zhou, Yunsheng Ma, Juanwu Lu, Lingxi Li, Yaobin Chen, Jitesh Panchal, Ziran Wang
We also validate that the proposed memory module considers personalized preferences and further reduces the takeover rate by up to 65. 2% compared with those without a memory module.
no code implementations • 16 Dec 2019 • Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis, Jitesh Panchal
We model the underlying information source as a fully-Bayesian, non-stationary Gaussian process (FBNSGP), and derive an approximation of the information gain of a hypothetical experiment about an arbitrary QoI conditional on the hyper-parameters The EIG about the same QoI is estimated by sample averages to integrate over the posterior of the hyper-parameters and the potential experimental outcomes.
1 code implementation • 14 Feb 2019 • Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis, Jitesh Panchal
We propose a novel methodology for high-dimensional uncertainty propagation of elliptic SPDEs which lifts the requirement for a deterministic forward solver.
Data Analysis, Statistics and Probability Computational Physics
1 code implementation • 26 Jul 2018 • Piyush Pandita, Ilias Bilionis, Jitesh Panchal
Our hypothesis is that an optimal BODE should be maximizing the expected information gain in the QoI.