| 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 | 97 | 2014 |
| Critical slowing down and hyperuniformity on approach to jamming S Atkinson, G Zhang, AB Hopkins, S Torquato Physical Review E 94 (1), 012902, 2016 | 79 | 2016 |
| Detailed characterization of rattlers in exactly isostatic, strictly jammed sphere packings S Atkinson, FH Stillinger, S Torquato Physical Review E 88 (6), 062208, 2013 | 57 | 2013 |
| 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 | 52 | 2019 |
| Maximally dense packings of two-dimensional convex and concave noncircular particles S Atkinson, Y Jiao, S Torquato Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 86 (3 …, 2012 | 52 | 2012 |
| Microstructure-statistics-property relations of anisotropic polydisperse particulate composites using tomography A Gillman, K Matouš, S Atkinson Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 87 (2 …, 2013 | 41 | 2013 |
| 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 | 39 | 2020 |
| 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 | 37 | 2019 |
| 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 | 19 | 2022 |
| 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 | 19 | 2016 |
| Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data S Atkinson arXiv preprint arXiv:2006.04228, 2020 | 13 | 2020 |
| 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 | 11 | 2021 |
| 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 | 7 | 2022 |
| Structured Bayesian Gaussian process latent variable model S Atkinson, N Zabaras arXiv preprint arXiv:1805.08665, 2018 | 5 | 2018 |
| 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 | 2 | 2020 |
| 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 | 1 | 2019 |
| 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 | | 2011 |
Salvatore TorquatoLewis Bernard Professor of Natural Sciences, Department of Chemistry, Physics and Materials ScienceVerified email at princeton.edu
