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Nicholas F. Marshall
Assistant Professor
Department of Mathematics
Oregon State University
Corvallis, Oregon
Email: marsnich@oregonstate.edu
Office: Kidder 292
Oregon
State University Directory Page
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
-
arXiv:2602.05155
Optimal Risk-Sharing Rules in Network-based
Decentralized Insurance
with Heather
Fogarty, Sooie-Hoe
Loke, Enrique
Thomann
-
arXiv:2511.21063
G-Net: A Provably Easy Construction of High-Accuracy
Random Binary Neural Networks
with Alireza
Aghasi,
Saeid Pourmand, Wyatt
Whiting
NeurIPS 2025
-
arXiv:2511.05364
Momentum accelerated power iterations and the restarted
Lanczos method
with
Alessandro Barletta, Sara
Pollock
-
arXiv:2510.24608
Random Walks, Faber Polynomials and Accelerated Power
Methods
with Peter
Cowal, Sara
Pollock
-
arXiv:2507.01885
Faber polynomials in a deltoid region and power
iteration momentum methods
with Peter
Cowal, Sara
Pollock
-
arXiv:2406.05922
Fast expansion into harmonics on the ball
with Joe
Kileel, Oscar
Mickelin, Amit Singer
SIAM Journal on Scientific Computing doi.org/10.1137/24M1668159
-
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
-
arXiv:2404.10759
Laplace-HDC: Understanding the geometry of binary
hyperdimensional computing
with
Saeid Pourmand, Wyatt
Whiting, Alireza
Aghasi
Journal of Artificial Intelligence Research doi.org/10.1613/jair.1.17688
-
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
-
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
-
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
-
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
-
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
-
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
-
arXiv:2201.13386
On a linearization of quadratic Wasserstein
distance
with
Philip Greengard, Jeremy Hoskins, Amit Singer
-
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
-
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
-
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
-
arXiv:1910.04201
Randomized mixed Hölder function approximation in
higher-dimensions
Technical Report
-
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
-
arXiv:1902.06633
A Cheeger inequality for graphs based on a
reflectionresearch principle
with
Edward Gelernt, Diana
Halikias, Charles
Kenney
Involve doi.org/10.2140/involve.2020.13.475
-
arXiv:1810.00823
Approximating mixed Hölder functions using random
samples
Annals of Applied Probability doi.org/10.1214/19-AAP1471
-
arXiv:1711.06711
Manifold learning with bi-stochastic kernels
with
Ronald Coifman
IMA Journal of Applied Mathematics doi.org/10.1093/imamat/hxy065
-
arXiv:1707.00682
Stretching convex domains to capture many lattice
points
International Mathematics Research Notices doi.org/10.1093/imrn/rny102
-
arXiv:1706.04170
Triangles capturing many lattice points
with Stefan
Steinerberger
Mathematika doi.org/10.1112/S0025579318000219
-
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
-
arXiv:1608.03628
Time Coupled Diffusion Maps
with Matthew
Hirn
Applied and Computational Harmonic Analysis doi.org/10.1016/j.acha.2017.11.003
-
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
-
some-math-for-numerics.pdf
Introductory note about some key mathematical ideas used in
numerical methods
Keywords: asymptotic series, Richardson extrapolation,
contraction mapping, and simple iteration
-
stirlings-approximation.pdf
Elementary proof of Stirling's approximation up to
constant
Keywords: concave functions, trapezoid rule, midpoint
rule
-
euler-maclaurin.pdf
Informal and precise statements of Euler-Maclaurin
formula
Preliminaries about asymptotic series, Richardson
extrapolation, Taylor's theorem, Trapezoid rule
-
gaussian-quadrature.pdf
Introduction to Gaussian quadrature
Keywords: Introduces Legendre polynomials, Gaussian
quadrature remainder formula, numerical example
-
chebyshev-interpolation.pdf
Introduction to polynomial interpolation
Keywords: polynomial interpolation remainder formula,
Chebyshev polynomials, Chebyshev nodes
-
de-moivre-thm.pdf Sketch of
de Moivre's central limit theorem
Keywords: Binomial distribution, Stirling's formula,
Reimann sum
Mentoring
Graduate Students
Undergraduate Summer Research
Teaching
- Winter 2026, Numerical Solution of ODEs, MTH 452/552,
Oregon State University
- Fall 2025, Advanced Calculus I, MTH 611, Oregon State
University
- Fall 2025, Numerical Linear Algebra, MTH 451/551, Oregon
State University
- Fall 2025, Probability I, MTH 463/563, Oregon State
University
- Spring 2025, Complex Analysis, MTH 611, Oregon State
University
- Winter 2025, Advanced Calculus II, MTH 312, Oregon State
University
- Winter 2025, Mathematics of Data Science, MTH 499/599,
Oregon State University
- Fall 2024, Probability Theory I, MTH 664, Oregon State
University
- Spring 2024, High Dimensional Probability, MTH 669,
Oregon State University
- Winter 2024, Probability Theory II, MTH 665, Oregon State
University
- Fall 2023, Probability Theory, MTH 664, Oregon State
University
- Spring 2023 Advanced Calculus II, MTH 312, Oregon State
University
- Spring 2023, Probability III, MTH 465/565, Oregon State
University
- Winter 2023, Probability II, MTH 464/564, Oregon State
University
- Fall 2021, Numerical methods, MAT 321/APC 321, Princeton
University
- Fall 2020, Numerical methods, MAT 321/APC 321, Princeton
University
- Spring 2021, Linear Algebra with Applications, MAT 202,
Princeton University
- Fall 2018, Calculus II, MATH 115, Yale University