Building Data-driven Models with Microstructural Images: Generalization
and Interpretability

Building Data-driven Models with Microstructural Images: Generalization and Interpretability

1 November 2017

Maxwell Hutchinson

Brian L. DeCost

Elizabeth A. Holm

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Papers citing "Building Data-driven Models with Microstructural Images: Generalization and Interpretability"

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Title
Manipulating Feature Visualizations with Gradient Slingshots Dilyara Bareeva Marina M.-C. Höhne Alexander Warnecke Lukas Pirch Klaus-Robert Müller Konrad Rieck Sebastian Lapuschkin Kirill Bykov AAML 76 6 0 11 Jan 2024
Leveraging Uncertainty from Deep Learning for Trustworthy Materials Discovery Workflows Jize Zhang B. Kailkhura T. Y. Han OOD 48 14 0 02 Dec 2020
Probabilistic modeling of discrete structural response with application to composite plate penetration models Anindya Bhaduri C. Meyer J. Gillespie B. Haque Michael D. Shields L. Graham‐Brady 44 9 0 23 Nov 2020
Image-driven discriminative and generative machine learning algorithms for establishing microstructure-processing relationships Wufei Ma E. Kautz Arun Baskaran Aritra Chowdhury V. Joshi B. Yener D. Lewis AI4CE 60 45 0 27 Jul 2020
Unsupervised machine learning via transfer learning and k-means clustering to classify materials image data R. Cohn Elizabeth A. Holm 59 65 0 16 Jul 2020
Overview: Computer vision and machine learning for microstructural characterization and analysis Elizabeth A. Holm R. Cohn Nan Gao Andrew R. Kitahara Thomas P. Matson Bo Lei Srujana Rao Yarasi 67 165 0 28 May 2020
Autonomous discovery in the chemical sciences part I: Progress Connor W. Coley Natalie S. Eyke K. Jensen 71 218 0 30 Mar 2020
Turbulent scalar flux in inclined jets in crossflow: counter gradient transport and deep learning modelling Pedro M. Milani Julia Ling J. Eaton 21 49 0 14 Jan 2020
An image-driven machine learning approach to kinetic modeling of a discontinuous precipitation reaction E. Kautz Wufei Ma S. Jana A. Devaraj V. Joshi B. Yener D. Lewis 32 21 0 13 Jun 2019