-
Active Learning via Bayesian Optimization for Materials Discovery
Online Presentations | 25 Jun 2021 | Contributor(s):: Hieu Doan, Garvit Agarwal
In this tutorial, we will demonstrate the use of active learning via Bayesian optimization (BO) to identify ideal molecular candidates for an energy storage application.
-
Bayesian optimization tutorial using Jupyter notebook
Tools | 11 Jun 2021 | Contributor(s):: Hieu Doan, Garvit Agarwal
Active learning via Bayesian optimization for materials discovery
-
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...
-
Aytekin Gel
https://nanohub.org/members/327168
-
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.
-
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.
-
ECE 595ML Lecture 13.2: Connecting Bayesian with Linear Regression
Online Presentations | 24 Mar 2020 | Contributor(s):: Stanley H. Chan
-
ECE 595ML Lecture 12.2: Bayesian Parameter Estimation - Choosing Priors
Online Presentations | 18 Mar 2020 | Contributor(s):: Stanley H. Chan
-
ECE 595ML Lecture 9.2: Bayesian Decision - Basic Principle
Online Presentations | 29 Feb 2020 | Contributor(s):: Stanley H. Chan
-
ECE 595ML Lecture 9.3: Bayesian Decision - The Three Cases
Online Presentations | 29 Feb 2020 | Contributor(s):: Stanley H. Chan
-
ECE 595ML Lecture 13.1: Connecting Bayesian with Linear Regression - Linear Regression Review
Online Presentations | 17 Feb 2020 | Contributor(s):: Stanley H. Chan
-
ECE 595ML Lecture 12.1: Bayesian Parameter Estimation - Basic Principles
Online Presentations | 14 Feb 2020 | Contributor(s):: Stanley H. Chan
-
Big Data in Reliability and Security: Applications
Online Presentations | 30 May 2019 | Contributor(s):: Saurabh Bagchi
-
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.
-
Calibration using DAKOTA
Tools | 21 Mar 2019 | Contributor(s):: Saaketh Desai, Alejandro Strachan
Uses DAKOTA to perform deterministic and Bayesian calibration
-
Literature transcriptomics review and data of Nanoparticle Induced Cellular Outcomes
Downloads | 07 Mar 2019 | Contributor(s):: Irini Furxhi
Data from in vitro differential gene expression analysis studies were gathered from peer-reviewed scientific literature. The studies gathered had a considerably variety of different human cell models including both primary cells and immortalized cell lines which exhibit varying...
-
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...
-
ME 597UQ Lecture 24: Bayesian Model Comparison using Sequential Monte Carlo
Online Presentations | 27 Apr 2018 | Contributor(s):: Ilias Bilionis
-
ME 597UQ Lecture 20: Inverse Problems/Model Calibration - Bayesian Approach
Online Presentations | 30 Mar 2018 | Contributor(s):: Ilias Bilionis
-
ME 597UQ Uncertainty Quantification
Courses | 02 Feb 2018 | Contributor(s):: Ilias Bilionis
The goal of this course is to introduce the fundamentals of uncertainty quantification to advanced undergraduates or graduate engineering and science students with research interests in the field of predictive modeling.