Daniel O'Malley | DeepAI

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Featured Co-authors

Francesco Ballarin
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Stephan Eidenbenz
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Youngsoo Choi
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Andreas Bärtschi
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Boian S. Alexandrov
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Jonghyun Lee
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Nikolaos Bouklas
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Jan Niklas Fuhg
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Teeratorn Kadeethum
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John Golden
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∙ 01/26/2023

The Quantum Alternating Operator Ansatz for Satisfiability Problems

We comparatively study, through large-scale numerical simulation, the pe...

0 John Golden, et al. ∙

∙ 10/21/2022

Quantum Algorithms for Geologic Fracture Networks

Solving large systems of equations is a challenge for modeling natural p...

0 Jessie M. Henderson, et al. ∙

∙ 06/21/2022

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

Avoiding over-pressurization in subsurface reservoirs is critical for ap...

36 Aleksandra Pachalieva, et al. ∙

∙ 02/11/2022

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

We propose a unified data-driven reduced order model (ROM) that bridges ...

5 Teeratorn Kadeethum, et al. ∙

∙ 02/01/2022

Evidence for Super-Polynomial Advantage of QAOA over Unstructured Search

We compare the performance of several variations of the Quantum Alternat...

0 John Golden, et al. ∙

∙ 06/25/2021

Threshold-Based Quantum Optimization

We propose and study Th-QAOA (pronounced Threshold QAOA), a variation of...

0 John Golden, et al. ∙

∙ 05/27/2021

A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networks

This work is the first to employ and adapt the image-to-image translatio...

16 Teeratorn Kadeethum, et al. ∙

∙ 01/08/2021

QAOA-based Fair Sampling on NISQ Devices

We study the status of fair sampling on Noisy Intermediate Scale Quantum...

0 John Golden, et al. ∙

∙ 08/31/2020

Homomorphic Encryption for Quantum Annealing with Spin Reversal Transformations

Homomorphic encryption has been an area of study in classical computing ...

0 Daniel O'Malley, et al. ∙

∙ 07/10/2020

Reverse Annealing for Nonnegative/Binary Matrix Factorization

It was recently shown that quantum annealing can be used as an effective...

0 John Golden, et al. ∙

∙ 06/06/2019

Learning to regularize with a variational autoencoder for hydrologic inverse analysis

Inverse problems often involve matching observational data using a physi...

0 Daniel O'Malley, et al. ∙

∙ 04/05/2017

Nonnegative/binary matrix factorization with a D-Wave quantum annealer

D-Wave quantum annealers represent a novel computational architecture an...

0 Daniel O'Malley, et al. ∙

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