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Steven Atkinson
Steven Atkinson
Amazon
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Titel
Zitiert von
Zitiert von
Jahr
Existence of isostatic, maximally random jammed monodisperse hard-disk packings
S Atkinson, FH Stillinger, S Torquato
Proceedings of the National Academy of Sciences 111 (52), 18436-18441, 2014
912014
Critical slowing down and hyperuniformity on approach to jamming
S Atkinson, G Zhang, AB Hopkins, S Torquato
Physical Review E 94 (1), 012902, 2016
702016
Detailed characterization of rattlers in exactly isostatic, strictly jammed sphere packings
S Atkinson, FH Stillinger, S Torquato
Physical Review E 88 (6), 062208, 2013
552013
Data-driven discovery of free-form governing differential equations
S Atkinson, W Subber, L Wang, G Khan, P Hawi, R Ghanem
arXiv preprint arXiv:1910.05117, 2019
482019
Maximally dense packings of two-dimensional convex and concave noncircular particles
S Atkinson, Y Jiao, S Torquato
Physical Review E 86 (3), 031302, 2012
462012
Microstructure-statistics-property relations of anisotropic polydisperse particulate composites using tomography
A Gillman, K Matouš, S Atkinson
Physical Review E 87 (2), 022208, 2013
402013
Structured Bayesian Gaussian process latent variable model: Applications to data-driven dimensionality reduction and high-dimensional inversion
S Atkinson, N Zabaras
Journal of Computational Physics 383, 166-195, 2019
372019
Advances in bayesian probabilistic modeling for industrial applications
S Ghosh, P Pandita, S Atkinson, W Subber, Y Zhang, NC Kumar, ...
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2020
352020
Static structural signatures of nearly jammed disordered and ordered hard-sphere packings: Direct correlation function
S Atkinson, FH Stillinger, S Torquato
Physical Review E 94 (3), 032902, 2016
172016
Inverse aerodynamic design of gas turbine blades using probabilistic machine learning
S Ghosh, G Anantha Padmanabha, C Peng, V Andreoli, S Atkinson, ...
Journal of Mechanical Design 144 (2), 021706, 2022
152022
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data
S Atkinson
arXiv preprint arXiv:2006.04228, 2020
112020
Pro-ML IDeAS: A Probabilistic Framework for Explicit Inverse Design using Invertible Neural Network
S Ghosh, GA Padmanabha, C Peng, S Atkinson, V Andreoli, P Pandita, ...
AIAA Scitech 2021 Forum, 0465, 2021
72021
Transfer Learning Based Modeling of Industrial Turbine Airfoil Characteristics
S Krishnan, S Ghosh, S Atkinson, V Andreoli, T Vandeputte, L Wang
AIAA SCITECH 2022 Forum, 2105, 2022
52022
Structured Bayesian Gaussian process latent variable model
S Atkinson, N Zabaras
arXiv preprint arXiv:1805.08665, 2018
52018
Bayesian task embedding for few-shot Bayesian optimization
S Atkinson, S Ghosh, N Chennimalai Kumar, G Khan, L Wang
AIAA Scitech 2020 Forum, 1145, 2020
22020
AIRFRAME DIGITAL TWIN (ADT) Delivery Order FA8650-17-F-2219: Scalable, Accurate, Flexible, Efficient, Robust, Prognostic and Probabilistic Individual Aircraft Tracking (SAFER …
L Wang, I Asher, S Atkinson, G Khan, R Longtin, D Ball, R Shannon, ...
GENERAL ELECTRIC CO NISKAYUNA NY NISKAYUNA United States, 2019
22019
A Probabilistic Machine Learning Framework for Explicit Inverse Design of Industrial Gas Turbine Blades
S Ghosh, V Andreoli, GA Padmanabha, C Peng, S Atkinson, P Pandita, ...
Turbo Expo: Power for Land, Sea, and Air 85031, V09BT27A003, 2021
2021
Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models
S Atkinson, Y Zhang, L Wang
arXiv preprint arXiv:2103.07502, 2021
2021
Structure and rigidity in maximally random jammed packings of hard particles
SD Atkinson
Princeton University, 2016
2016
Three-Dimensional Characterization of Polydisperse Particulate Composites from Microtomography
S Atkinson, ILLINOISROCSTAR LLC CHAMPAIGN IL
2011
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