D. O'Malley

发表

A universal field equation for dispersive processes in heterogeneous media

J. H. Cushman, Moongyu Park, M. Moroni, 2011 .

Achieving fair sampling in quantum annealing

D. O'Malley, C. Nehrkorn, Vaibhaw Kumar, 2020, 2007.08487.

Contaminant source identification using semi-supervised machine learning.

D. O'Malley, V. Vesselinov, B. Alexandrov, 2017, Journal of contaminant hydrology.

Reduced-order modeling through machine learning and graph-theoretic approaches for brittle fracture applications

Bryan A. Moore, Roselyne B. Tchoua, H. Viswanathan, 2019, Computational Materials Science.

Nonnegative tensor factorization for contaminant source identification.

D. O'Malley, V. Vesselinov, B. Alexandrov, 2019, Journal of contaminant hydrology.

On generating conductivity fields with known fractal dimension and nonstationary increments

John H. Cushman, Daniel O'Malley, Patrick O'Rear, 2012 .

A Method for Identifying Diffusive Trajectories with Stochastic Models

J. H. Cushman, D. O'Malley, V. Vesselinov, 2014 .

Large‐scale inverse model analyses employing fast randomized data reduction

Velimir V. Vesselinov, Tan Bui-Thanh, Ellen B. Le, 2017 .

Tucker-1 Boolean Tensor Factorization with Quantum Annealers

H. Djidjev, D. O'Malley, B. Alexandrov, 2020, 2020 International Conference on Rebooting Computing (ICRC).

Push‐pull tracer tests: Their information content and use for characterizing non‐Fickian, mobile‐immobile behavior

D. O'Malley, S. Karra, B. Berkowitz, 2016 .

Analytical solutions for anomalous dispersion transport

Velimir V. Vesselinov, Daniel O'Malley, D. O'Malley, 2014 .

Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture pdf

Daniel O'Malley, M. Giselle Fern'andez-Godino, Tanmoy Bhattacharya, 2020, Computational Materials Science.

Accelerating high-strain continuum-scale brittle fracture simulations with machine learning

R. Haftka, D. O'Malley, A. Hunter, 2021 .

QAOA-based Fair Sampling on NISQ Devices pdf

Stephan Eidenbenz, Andreas Bärtschi, Daniel O'Malley, 2021, ArXiv.

Sampling on NISQ Devices: "Who’s the Fairest One of All?"

John K. Golden, D. O'Malley, S. Eidenbenz, 2021, 2021 IEEE International Conference on Quantum Computing and Engineering (QCE).

Random Renormalization Group Operators Applied to Stochastic Dynamics

J. H. Cushman, D. O'Malley, D. O’Malley, 2012 .

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management

H. Viswanathan, D. O'Malley, D. Harp, 2022, ArXiv.

Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties

H. Viswanathan, D. O'Malley, N. Bouklas, 2021, Comput. Geosci..

Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management

H. Viswanathan, D. O'Malley, D. Harp, 2022, Scientific Reports.

AI for Extreme Volcanic Climate Forcing and Feedback Forecasting in the 21st century

M. Dubey, P. Chylek, H. Viswanathan, 2021 .

Transient flow modeling in fractured media using graphs.

H. Viswanathan, D. O'Malley, S. Karra, 2020, Physical review. E.

Robust decision analysis for environmental management of groundwater contamination sites

D. O'Malley, V. Vesselinov, D. Katzman, 2013, 1311.6014.

Nonlocal Models for Transport in Fractal Media

J. H. Cushman, D. O'Malley, 2017 .