Nicholas F. Marshall

nick.jpg

Assistant Professor
Department of Mathematics
Oregon State University

Email: [email protected]
Office: Kidder 292
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Research interests

I am interested in problems that involve an interplay between analysis, geometry, and probability (especially such problems motivated by data science).

About

Research

  1. arXiv:2406.05922
    Fast expansion into harmonics on the ball
    with Joe Kileel, Oscar Mickelin, Amit Singer
    SIAM Journal on Scientific Computing (to appear)
  2. arXiv:2406.01552
    Learning equivariant tensor functions with applications to sparse vector recovery
    with Wilson G. Gregory, Josué Tonelli-Cueto, Andrew S. Lee, Soledad Villar
  3. arXiv:2404.10759
    Laplace-HDC: Understanding the geometry of binary hyperdimensional computing
    with Saeid Pourmand, Wyatt Whiting, Alireza Aghasi
  4. arXiv:2401.15183
    Moment-based metrics for molecules computable from cryo-EM images
    with Andy Zhang, Oscar Mickelin, Joe Kileel, Eric Verbeke, Marc Gilles, Amit Singer
    Biological Imaging doi.org/10.1017/S2633903X24000023
  5. arXiv:2401.09415
    Randomized Kaczmarz with geometrically smoothed momentum
    with Seth Alderman, Roan Luikart
    SIAM Journal on Matrix Analysis and Applications doi.org/10.1137/24M1633820
  6. arXiv:2212.14288
    From the binomial reshuffling model to Poisson distribution of money
    with Fei Cao
    Networks and Heterogeneous Media doi.org/10.3934/nhm.2024002
  7. arXiv:2210.17501
    Fast Principal Component Analysis for Cryo-EM Images
    with Oscar Mickelin, Yunpeng Shi, Amit Singer
    Biological Imaging doi.org/10.1017/S2633903X23000028
  8. arXiv:2207.13674
    Fast expansion into harmonics on the disk: a steerable basis with fast radial convolutions
    with Oscar Mickelin, Amit Singer
    SIAM Journal on Scientific Computing doi.org/10.1137/22M1542775
  9. arXiv:2202.12224
    An optimal scheduled learning rate for a randomized Kaczmarz algorithm
    with Oscar Mickelin
    SIAM Journal on Matrix Analysis and Applications doi.org/10.1137/22M148803X
  10. arXiv:2201.13386
    On a linearization of quadratic Wasserstein distance
    with Philip Greengard, Jeremy Hoskins, Amit Singer
  11. arXiv:2107.14747
    A common variable minimax theorem for graphs
    with Ronald Coifman, Stefan Steinerberger
    Foundations of Computational Mathematics doi.org/10.1007/s10208-022-09558-8
  12. arXiv:2101.07709
    Multi-target detection with rotations
    with Tamir Bendory, Ti-Yen Lan, Iris Rukshin, Amit Singer
    Inverse Problems and Imaging doi.org/10.3934/ipi.2022046
  13. arXiv:1910.10006
    Image recovery from rotational and translational invariants
    with Tamir Bendory, Ti-Yen Lan, Amit Singer
    ICASSP doi.org/10.1109/ICASSP40776.2020.9053932
  14. arXiv:1910.04201
    Randomized mixed Hölder function approximation in higher-dimensions
    Technical Report
  15. arXiv:1907.03873
    A fast simple algorithm for computing the potential of charges on a line
    with Zydrunas Gimbutas, Vladimir Rokhlin
    Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2020.06.002
  16. arXiv:1902.06633
    A Cheeger inequality for graphs based on a reflection principle
    with Edward Gelernt, Diana Halikias, Charles Kenney
    Involve doi.org/10.2140/involve.2020.13.475
  17. arXiv:1810.00823
    Approximating mixed Hölder functions using random samples
    Annals of Applied Probability doi.org/10.1214/19-AAP1471
  18. arXiv:1711.06711
    Manifold learning with bi-stochastic kernels
    with Ronald Coifman
    IMA Journal of Applied Mathematics doi.org/10.1093/imamat/hxy065
  19. arXiv:1707.00682
    Stretching convex domains to capture many lattice points
    International Mathematics Research Notices doi.org/10.1093/imrn/rny102
  20. arXiv:1706.04170
    Triangles capturing many lattice points
    with Stefan Steinerberger
    Mathematika doi.org/10.1112/S0025579318000219
  21. arXiv:1704.02962
    The Stability of the First Neumann Laplacian Eigenfunction Under Domain Deformations and Applications
    Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2019.05.001
  22. arXiv:1608.03628
    Time Coupled Diffusion Maps
    with Matthew Hirn
    Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2017.11.003
  23. arXiv:1607.05235
    Extracting Geography from Trade Data
    with Yuke Li, Tianhao Wu, Stefan Steinerberger
    Physica A doi.org/10.1016/j.physa.2017.01.037

Notes

Some short notes on various topics

Mentoring

Teaching