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Nicholas Zabaras

Affiliations:

Cornell University, Ithaca, NY, United States

Area:

Mechanical Engineering, Statistics

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"Nicholas Zabaras"

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Parents

Children

Nicholas Geneva	grad student		Notre Dame
Srikanth Akkaram	grad student	2001	Cornell
Rajiv Sampath	grad student	2001	Cornell
Shankar Ganapathysubramanian	grad student	2004	Cornell
Jingbo Wang	grad student	2005	Cornell
Swagato Acharjee	grad student	2006	Cornell
Deep Samanta	grad student	2006	Cornell
Badrinarayanan Velamur Asokan	grad student	2006	Cornell
Veeraraghavan Sundararaghavan	grad student	2007	Cornell
Lijian Tan	grad student	2007	Cornell
Baskar Ganapathysubramanian	grad student	2008	Cornell
Sethuraman Sankaran	grad student	2008	Cornell
Babak Kouchmeshky	grad student	2010	Cornell
Xiang Ma	grad student	2010	Cornell
Jiang Wan	grad student	2013	Cornell
Bin Wen	grad student	2013	Cornell

Collaborators

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Publications

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Geneva N, Zabaras N. (2021) Transformers for modeling physical systems. Neural Networks : the Official Journal of the International Neural Network Society. 146: 272-289
Mo S, Zabaras N, Shi X, et al. (2020) Integration of Adversarial Autoencoders With Residual Dense Convolutional Networks for Estimation of Non‐Gaussian Hydraulic Conductivities Water Resources Research. 56
Schöberl M, Zabaras N, Koutsourelakis PS. (2019) Predictive collective variable discovery with deep Bayesian models. The Journal of Chemical Physics. 150: 024109
Mo S, Zabaras N, Shi X, et al. (2019) Deep Autoregressive Neural Networks for High-Dimensional Inverse Problems in Groundwater Contaminant Source Identification Water Resources Research. 55: 3856-3881
Mo S, Zhu Y, Zabaras N, et al. (2019) Deep Convolutional Encoder‐Decoder Networks for Uncertainty Quantification of Dynamic Multiphase Flow in Heterogeneous Media Water Resources Research. 55: 703-728
Geneva N, Zabaras N. (2019) Modeling the dynamics of PDE systems with physics-constrained deep auto-regressive networks Journal of Computational Physics. 403: 109056
Zhu Y, Zabaras N, Koutsourelakis P, et al. (2019) Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data Journal of Computational Physics. 394: 56-81
Geneva N, Zabaras N. (2019) Quantifying model form uncertainty in Reynolds-averaged turbulence models with Bayesian deep neural networks Journal of Computational Physics. 383: 125-147
Atkinson S, Zabaras N. (2019) Structured Bayesian Gaussian process latent variable model: Applications to data-driven dimensionality reduction and high-dimensional inversion Journal of Computational Physics. 383: 166-195
Lee W, Zabaras N. (2018) Parallel probabilistic graphical model approach for nonparametric Bayesian inference Journal of Computational Physics. 372: 546-563

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