Daniel O'Malley

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 45

Top Topics

Quantum Computing

Machine Learning

Top Venues

SIAM/ASA J. Uncertain. Quantification

Publications

Manish Bhattarai, Javier E. Santos, Shawn Jones, Ayan Biswas, Boian S. Alexandrov, Daniel O'Malley
Enhancing Code Translation in Language Models with Few-Shot Learning via Retrieval-Augmented Generation. CoRR (2024)
Zhiwei Ma, Javier E. Santos, Greg Lackey, Hari S. Viswanathan, Daniel O'Malley
Information Extraction from Historical Well Records Using A Large Language Model. CoRR (2024)
Aleksandra Pachalieva, Jeffrey D. Hyman, Daniel O'Malley, Hari S. Viswanathan, Gowri Srinivasan
Learning the Factors Controlling Mineralization for Geologic Carbon Sequestration. CoRR (2023)
Javier E. Santos, Zachary R. Fox, Arvind Mohan, Daniel O'Malley, Hari S. Viswanathan, Nicholas Lubbers
Development of the Senseiver for efficient field reconstruction from sparse observations. Nat. Mac. Intell. 5 (11) (2023)
Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Hongkyu Yoon
Progressive reduced order modeling: empowering data-driven modeling with selective knowledge transfer. CoRR (2023)
Agnese Marcato, Daniel O'Malley, Hari S. Viswanathan, Eric Guiltinan, Javier E. Santos
Reconstruction of Fields from Sparse Sensing: Differentiable Sensor Placement Enhances Generalization. CoRR (2023)
Christo Meriwether Keller, Stephan J. Eidenbenz, Andreas Bärtschi, Daniel O'Malley, John K. Golden, Satyajayant Misra
Hierarchical Multigrid Ansatz for Variational Quantum Algorithms. CoRR (2023)
John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
The Quantum Alternating Operator Ansatz for Satisfiability Problems. CoRR (2023)
Sarah Y. Greer, Daniel O'Malley
Early steps toward practical subsurface computations with quantum computing. Frontiers Comput. Sci. 5 (2023)
Aleksei G. Sorokin, Aleksandra Pachalieva, Daniel O'Malley, James M. Hyman, Fred J. Hickernell, Nicolas W. Hengartner
Computationally Efficient and Error Aware Surrogate Construction for Numerical Solutions of Subsurface Flow Through Porous Media. CoRR (2023)
John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
The Quantum Alternating Operator Ansatz for Satisfiability Problems. QCE (2023)
Daniel O'Malley, Sarah Y. Greer, Aleksandra Pachalieva, Wu Hao, Dylan Robert Harp, Velimir V. Vesselinov
DPFEHM: a differentiable subsurface physics simulator. J. Open Source Softw. 8 (90) (2023)
John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
Numerical Evidence for Exponential Speed-Up of QAOA over Unstructured Search for Approximate Constrained Optimization. QCE (2023)
Marta D'Elia, Hang Deng, Cedric G. Fraces, Krishna Garikipati, Lori Graham-Brady, Amanda A. Howard, George Em Karniadakis, Vahid Keshavarzzadeh, Robert M. Kirby, J. Nathan Kutz, Chunhui Li, Xing Liu, Hannah Lu, Pania Newell, Daniel O'Malley, Masa Prodanovic, Gowri Srinivasan, Alexandre M. Tartakovsky, Daniel M. Tartakovsky, Hamdi A. Tchelepi, Bozo Vazic, Hari S. Viswanathan, Hongkyu Yoon, Piotr Zarzycki
Machine Learning in Heterogeneous Porous Materials. CoRR (2022)
Jessie M. Henderson, Marianna Podzorova, M. Cerezo, John K. Golden, Leonard Gleyzer, Hari S. Viswanathan, Daniel O'Malley
Quantum Algorithms for Geologic Fracture Networks. CoRR (2022)
Teeratorn Kadeethum, Daniel O'Malley, Youngsoo Choi, Hari S. Viswanathan, Nikolaos Bouklas, Hongkyu Yoon
Continuous conditional generative adversarial networks for data-driven solutions of poroelasticity with heterogeneous material properties. Comput. Geosci. 167 (2022)
Aleksandra Pachalieva, Daniel O'Malley, Dylan Robert Harp, Hari S. Viswanathan
Physics-informed machine learning with differentiable programming for heterogeneous underground reservoir pressure management. CoRR (2022)
John K. Golden, Andreas Bärtschi, Stephan J. Eidenbenz, Daniel O'Malley
Evidence for Super-Polynomial Advantage of QAOA over Unstructured Search. CoRR (2022)
Teeratorn Kadeethum, Francesco Ballarin, Daniel O'Malley, Youngsoo Choi, Nikolaos Bouklas, Hongkyu Yoon
Reduced order modeling with Barlow Twins self-supervised learning: Navigating the space between linear and nonlinear solution manifolds. CoRR (2022)
Elijah Pelofske, John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
Sampling on NISQ Devices: "Who's the Fairest One of All?". QCE (2021)
Jessie M. Henderson, Daniel O'Malley, Hari S. Viswanathan
Interrogating the performance of quantum annealing for the solution of steady-state subsurface flow. HPEC (2021)
John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
QAOA-based Fair Sampling on NISQ Devices. CoRR (2021)
Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. Nat. Comput. Sci. 1 (12) (2021)
John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
Threshold-Based Quantum Optimization. QCE (2021)
Elijah Pelofske, John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
Sampling on NISQ Devices: "Who's the Fairest One of All?". CoRR (2021)
Elijah Pelofske, Georg Hahn, Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov
Boolean Hierarchical Tucker Networks on Quantum Annealers. LSSC (2021)
Teeratorn Kadeethum, Francesco Ballarin, Y. Choi, Daniel O'Malley, H. Yoon, Nikolaos Bouklas
Non-intrusive reduced order modeling of natural convection in porous media using convolutional autoencoders: comparison with linear subspace techniques. CoRR (2021)
John K. Golden, Andreas Bärtschi, Daniel O'Malley, Stephan J. Eidenbenz
Threshold-Based Quantum Optimization. CoRR (2021)
Teeratorn Kadeethum, Daniel O'Malley, Jan Niklas Fuhg, Youngsoo Choi, Jonghyun Lee, Hari S. Viswanathan, Nikolaos Bouklas
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks. CoRR (2021)
Elijah Pelofske, Georg Hahn, Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov
Quantum Annealing Algorithms for Boolean Tensor Networks. CoRR (2021)
John K. Golden, Daniel O'Malley
Pre- and post-processing in quantum-computational hydrologic inverse analysis. Quantum Inf. Process. 20 (5) (2021)
Elijah Pelofske, Georg Hahn, Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov
Boolean Hierarchical Tucker Networks on Quantum Annealers. CoRR (2021)
Maruti Kumar Mudunuru, Daniel O'Malley, Shriram Srinivasan, Jeffrey D. Hyman, Matthew R. Sweeney, Luke Frash, Bill Carey, Michael R. Gross, Nathan J. Welch, Satish Karra, Velimir V. Vesselinov, Qinjun Kang, Hongwu Xu, Rajesh J. Pawar, Tim Carr, Liwei Li, George D. Guthrie, Hari S. Viswanathan
Physics-Informed Machine Learning for Real-time Reservoir Management. AAAI Spring Symposium: MLPS (2020)
Daniel O'Malley, John K. Golden
Homomorphic Encryption for Quantum Annealing with Spin Reversal Transformations. CoRR (2020)
Nishant Panda, Dave Osthus, Gowri Srinivasan, Daniel O'Malley, Viet T. Chau, Diane Oyen, Humberto Godinez
Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling. J. Comput. Phys. 420 (2020)
Daniel O'Malley, John K. Golden
Homomorphic Encryption for Quantum Annealing with Spin Reversal Transformations. HPEC (2020)
John K. Golden, Daniel O'Malley
Reverse Annealing for Nonnegative/Binary Matrix Factorization. CoRR (2020)
Cristina Garcia-Cardona, M. Giselle Fernández-Godino, Daniel O'Malley, Tanmoy Bhattacharya
Uncertainty Bounds for Multivariate Machine Learning Predictions on High-Strain Brittle Fracture. CoRR (2020)
Daniel O'Malley, Hristo N. Djidjev, Boian S. Alexandrov
Tucker-1 Boolean Tensor Factorization with Quantum Annealers. ICRC (2020)
John K. Golden, Daniel O'Malley
Pre- and post-processing in quantum-computational hydrologic inverse analysis. CoRR (2019)
Daniel O'Malley, John K. Golden, Velimir V. Vesselinov
Learning to regularize with a variational autoencoder for hydrologic inverse analysis. CoRR (2019)
Elizabeth Qian, Benjamin Peherstorfer, Daniel O'Malley, Velimir V. Vesselinov, Karen Willcox
Multifidelity Monte Carlo Estimation of Variance and Sensitivity Indices. SIAM/ASA J. Uncertain. Quantification 6 (2) (2018)
Hristo N. Djidjev, Daniel O'Malley, Hari S. Viswanathan, Jeffrey D. Hyman, Satish Karra, Gowri Srinivasan
Learning on Graphs for Predictions of Fracture Propagation, Flow and Transport. IPDPS Workshops (2017)
Daniel O'Malley, Velimir V. Vesselinov, Boian S. Alexandrov, Ludmil B. Alexandrov
Nonnegative/binary matrix factorization with a D-Wave quantum annealer. CoRR (2017)
Daniel O'Malley, Velimir V. Vesselinov
ToQ.jl: A high-level programming language for D-Wave machines based on Julia. HPEC (2016)
Daniel O'Malley, Velimir V. Vesselinov
A Combined Probabilistic/Nonprobabilistic Decision Analysis for Contaminant Remediation. SIAM/ASA J. Uncertain. Quantification 2 (1) (2014)