Articles
Quantum Computation and Quantum Information#
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1. Application-level Benchmarking of Quantum Computers using Nonlocal Game Strategies#
(with Jim Furches, Sarah Chehade, Kathleen E Hamilton, Nathan Wiebe)
Expanded Version of “Variational Methods for Computing NonLocal Quantum Strategies”
Quantum Science and Technology[Paper] [arXiv] [Repo] [Poster (by Jim Furches)]
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2. Adaptive Quantum Generative Training using an Unbounded Loss Function#
(with Kyle Sherbert, Jim Furches, Karunya Shirali, Sophia E. Economou)
IEEE International Conference on Quantum Computing and Engineering (QCE24)
IEEE Best Paper Award
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3. A Lie Algebraic Theory of Barren Plateaus for Deep Parameterized Quantum Circuits#
(with Michael Ragone, Bojko N. Bakalov, Frédéric Sauvage, Alexander F. Kemper, Martin Larocca, Marco Cerezo)
Nature Communications[Paper] [arXiv] [Press Release]
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4. Generating Approximate Ground States of Molecules Using Quantum Machine Learning#
(with Jack Ceroni, Torin F. Stetina, Mária Kieferová, Juan Miguel Arrazola, Nathan Wiebe)
Submitted
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5. Quantum Generative Training using Rényi Divergences#
(with Mária Kieferová, Nathan Wiebe)
Submitted
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6. Entanglement Induced Barren Plateaus#
(with Mária Kieferová, Nathan Wiebe)
PRX Quantum
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7. Classification of Rank 5 Premodular Categories#
(with Paul Bruilard)
Journal of Mathematical Physics[Paper] [arXiv] [Slides (JMM 2017)]
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8. Quantum Graph Homomorphisms via Operator Systems#
(with Vern Paulsen)
Linear Algebra and its Applications[Paper] [arXiv] [Slides (Barcelona 2015)] [Slides (JMM 2016)]
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9. Lovász Theta Type Norms and Operator Systems#
(with Vern Paulsen)
Linear Algebra and its Applications[Paper] [arXiv] [Slides (JMM 2015)]
Data Science and Machine Learning#
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10. Using Skew to Assess the Quality of GAN-generated Image Features#
(with Lorenzo Luzi, Helen Jenne, Ryan Murray)
Transactions on Machine Learning Research
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11. Seven Open Problems in Applied Combinatorics#
(with Sinan G. Aksoy, Ryan Bennink, Yuzhou Chen, José Frías, Yulia R. Gel, Bill Kay, Uwe Naumann, Anthony V. Petyuk, Sandip Roy, Ignacio Segovia-Dominguez, Nate Veldt, Stephen J. Young)
Journal of Combinatorics
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12. The SVD of Convolutional Weights: A CNN Interpretability Framework#
(with Brenda Praggastis, Davis Brown, Emilie Purvine, Madelyn Shapiro, Bei Wang)
Submitted
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13. Evaluating generative networks using Gaussian mixtures of image features#
(with Lorenzo Luzi, Nile Wynar, Richard Baraniuk, Michael Henry)
WACV 2023
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14. Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven Modeling of Air Pollutants#
(with Javier Rubio-Herrero, Louis Fan)
Journal of Cleaner Production
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15. Application of entropy and signal energy for ultrasound-based classification of three-dimensional printed polyetherketoneketone components#
(with with Francesco Luzi, Michelle Fenn, Joseph Christ, Zachary Kennedy, Tamas Varga, Michael Hughes)
The Journal of the Acoustical Society of America[Paper]
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16. Tracking the Chemical Evolution of Iodine Species Using Recurrent Neural Networks#
(with Jenna Bilbrey, Michel Sassi, Andrew Ritzmann, Neil Henson, Malachi Schram)
ACS Omega[Paper] [Press Release]
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17. Robust Assessment of Real-World Adversarial Examples#
(with Brett Jefferson)
CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision
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18. Hypernetwork Science via High-Order Hypergraph Walks#
(with Sinan Aksoy, Cliff Joslyn, Brenda Praggastis, Emilie Purvine)
EPJ Data Science
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19. Physics‐Informed Deep Neural Networks for Learning Parameters and Constitutive Relationships in Subsurface Flow Problems#
(with Alexandre Tartakovsky, Paris Perdikaris, Guzel Tartakovsky, David Barajas-Solano)
Water Resources Research
