All Categories (1-20 of 23)

1. Autonomous Neutron Diffraction Experiments with ANDiE

   Online Presentations | 14 Nov 2021 | Contributor(s):: Austin McDannald

   This tutorial will cover the working principles of ANDiE, how physics was encoded into the design, and demonstrate how ANDiE can be used to autonomously control neutron diffraction experiments.

2. Autonomous Neutron Diffraction Explorer

   Tools | 01 Nov 2021 | Contributor(s):: Austin McDannald

   Autonomously control neutron diffraction experiments to discover order parameter.

3. Batch Reification Fusion Optimization (BAREFOOT) Framework

   Online Presentations | 09 Jun 2021 | Contributor(s):: Richard Couperthwaite

   This tutorial will present the fundamentals of multi-fidelity fusion as well as Sequential and Batch Bayesian Optimization as possible optimization approaches that can be integrated with high accuracy computational models or experimental procedures to speed up the optimization or design of...

4. A Batch Reification/Fusion Optimization Framework for Bayesian-based Material Optimization

   Tools | 27 Apr 2021 | Contributor(s):: Richard Couperthwaite, Raymundo Arroyave

   This tool is a Bayesian optimization framework that allows for a combination of a multi-fidelity (Reification/Fusion) optimization approach with a Batch Bayesian Approach.

5. Uncertainty Quantification and Scientific Machine Learning for Complex Engineering Systems

   Online Presentations | 17 Aug 2020 | Contributor(s):: Guang Lin

   In this talk, I will first present a review of the novel UQ techniques I developed to conduct stochastic simulations for very large-scale complex systems.

6. ECE 595ML Lecture 13.2: Connecting Bayesian with Linear Regression

   Online Presentations | 24 Mar 2020 | Contributor(s):: Stanley H. Chan

7. ECE 595ML Lecture 12.2: Bayesian Parameter Estimation - Choosing Priors

   Online Presentations | 18 Mar 2020 | Contributor(s):: Stanley H. Chan

8. ECE 595ML Lecture 9.2: Bayesian Decision - Basic Principle

   Online Presentations | 29 Feb 2020 | Contributor(s):: Stanley H. Chan

9. ECE 595ML Lecture 9.3: Bayesian Decision - The Three Cases

   Online Presentations | 29 Feb 2020 | Contributor(s):: Stanley H. Chan

10. ECE 595ML Lecture 13.1: Connecting Bayesian with Linear Regression - Linear Regression Review

    Online Presentations | 17 Feb 2020 | Contributor(s):: Stanley H. Chan

11. ECE 595ML Lecture 12.1: Bayesian Parameter Estimation - Basic Principles

    Online Presentations | 14 Feb 2020 | Contributor(s):: Stanley H. Chan

12. Human-Interpretable Concept Learning via Information Lattices

    Online Presentations | 23 May 2019 | Contributor(s):: Lav R. Varshney

    The basic idea is an iterative discovery algorithm that has a student-teacher architecture and that operates on a generalization of Shannon’s information lattice, which itself encodes a hierarchy of abstractions and is algorithmically constructed from group-theoretic foundations.

13. Magnetic Tunnel Junction (MTJ) as Stochastic Neurons and Synapses: Stochastic Binary Neural Networks, Bayesian Inferencing, Optimization Problems

    Online Presentations | 26 Oct 2018 | Contributor(s):: Abhronil Sengupta, Kaushik Roy

    In this presentation, we provide a multi-disciplinary perspective across the stack of devices, circuits, and algorithms to illustrate how the stochastic switching dynamics of spintronic devices in the presence of thermal noise can provide a direct mapping to the units of such computing...

14. ME 597UQ Lecture 24: Bayesian Model Comparison using Sequential Monte Carlo

    Online Presentations | 27 Apr 2018 | Contributor(s):: Ilias Bilionis

15. Efficient Exploration of Quantified Uncertainty in Granular Crystals

    Online Presentations | 16 Mar 2016 | Contributor(s):: Juan Camilo Lopez

    This work presents a way of quantifying uncertainty in granular crystals in a computationally efficient way. To accomplish this, a low dimensional response surface is approximated through the method of active subspaces. Within this framework, special structure within the inputs is exploited to...

16. Granular Crystals

    Tools | 22 Jul 2015 | Contributor(s):: Juan Camilo Lopez, Rohit Kaushal Tripathy, Ilias Bilionis, Marcial Gonzalez

    Allows the user to sample properties of granular chains under uncertainty propagation

17. Cluster Optimization BGO 01

    Tools | 29 Jul 2015 | Contributor(s):: Ilias Bilionis, Yinuo Li

    Cluster Optimization Using Bayesian Global Optimization

18. Gaussian process regression in 1D

    Tools | 26 Nov 2014 | Contributor(s):: Ilias Bilionis, Alejandro Strachan, Benjamin P Haley, Martin Hunt, Rohit Kaushal Tripathy, Sam Reeve

    Use Gaussian processes to represent x-y data

19. IMA 2013 UQ: Bayesian Approaches for Spatial- Stochastic Basis Selection: Applications to Fuel Cell Predictive Modeling

    Online Presentations | 13 Mar 2014 | Contributor(s):: Guang Lin

    In this talk, two fully Bayesian methods (Bayesian uncertainty method and Bayesian mixture procedure) will be introduced that can evaluate generalized Polynomial Chaos (gPC) expansions in both stochastic and spatial domains when the number of the available basis functions is significantly larger...

20. [Illinois] Intravoxel Incoherent Motion (IVIM) for Quantification of Microcirculatory Flow

    Online Presentations | 26 Feb 2014 | Contributor(s):: Alex Cerjanic

    Diffusion weighted Magnetic Resonance Imaging (DW-MRI) is an increasingly popular tool used to probe the microscopic structure of materials and biological tissues. Most studies employing DW-MRI rely on the passive diffusion of water molecules to interrogate the structure of the object or tissue...