Quantum Computation and Quantum Information⌗

  

• 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)

  [arXiv] [Repo]

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• Variational Methods for Computing Non-Local Quantum Strategies⌗

  (with Jim Furches, Nathan Wiebe)
  Submitted

  [arXiv] [Repo] [Poster (by Jim Furches)]

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• 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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• Generating Approximate Ground States of Molecules Using Quantum Machine Learning⌗

  (with Jack Ceroni, Torin F. Stetina, Mária Kieferová, Juan Miguel Arrazola, Nathan Wiebe)
  Submitted

  [arXiv] [Repo]

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• Quantum Generative Training using Rényi Divergences⌗

  (with Mária Kieferová, Nathan Wiebe)
  Submitted

  [arXiv] [Repo]

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• Entanglement Induced Barren Plateaus⌗

  (with Mária Kieferová, Nathan Wiebe)
  PRX Quantum

  [Paper] [arXiv] [Poster (by Mária Kieferová)]

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• Classification of Rank 5 Premodular Categories⌗

  (with Paul Bruilard)
  Journal of Mathematical Physics

  [Paper] [arXiv] [Slides (JMM 2017)]

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• 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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• 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⌗

  

• Using Skew to Assess the Quality of GAN-generated Image Features⌗

  (with Lorenzo Luzi, Helen Jenne, Ryan Murray)

  Transactions on Machine Learning Research

  [Paper, arXiv]

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• 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

  [Paper, arXiv]

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• The SVD of Convolutional Weights: A CNN Interpretability Framework⌗

  (with Brenda Praggastis, Davis Brown, Emilie Purvine, Madelyn Shapiro, Bei Wang)
  Submitted

  [arXiv] [Repo]

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• Evaluating generative networks using Gaussian mixtures of image features⌗

  (with Lorenzo Luzi, Nile Wynar, Richard Baraniuk, Michael Henry)
  WACV 2023

  [Paper] [arXiv] [Poster (by Lorenzo Luzi)]

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• Modeling Atmospheric Data and Identifying Dynamics: Temporal Data-Driven Modeling of Air Pollutants⌗

  (with Javier Rubio-Herrero, Louis Fan)
  Journal of Cleaner Production

  [Paper] [arXiv] [Poster]

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• 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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• 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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• Robust Assessment of Real-World Adversarial Examples⌗

  (with Brett Jefferson)
  CVPR 2020 Workshop on Adversarial Machine Learning in Computer Vision

  [Paper] [arXiv] [Talk] [Slides]

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• Hypernetwork Science via High-Order Hypergraph Walks⌗

  (with Sinan Aksoy, Cliff Joslyn, Brenda Praggastis, Emilie Purvine)
  EPJ Data Science

  [Paper] [arXiv]

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• 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

  [Paper] [arXiv] [Slides] [Repo]

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• On the structure of isometrically embeddable metric spaces⌗

  (with Stephen Young, Kathleen Nowak)
  Electronic Journal of Linear Algebra

  [Paper] [arXiv]