Publications & presentations
Follow the links to see publications and presentations
Published articles
[3] P. Melland, R. Curtu, and Z. Aminzare, "Spike-Adding Mechanisms in a Three-Timescale System: Insights from the FitzHugh-Nagumo Model with Periodic Forcing" To appear in: SIAM Journal on Applied Dynamical Systems. [Arxiv].
[2] P. Melland and R. Curtu, "Attractor-like dynamics extracted from human electrocorticographic recordings underlie computational principles of auditory bistable perception," Accepted in: The Journal of Neuroscience. [doi.org/10.1523/JNEUROSCI.1531-22.2023].[pdf]
[1] P. Melland, J. Albright, and N.M. Urban, "Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamic scheme," Mach. Learn.: Sci. Technol. [doi.org/10.1088/2632-2153/abd644]. [pdf]
Manuscripts in progress
[4] P. Melland and A. Barrerio, "Multiscale and decoupled spike sorting for tetrodes."
Poster presentations
Exploring fast and slow neural correlates of auditory perceptual bistability with diffusion-mapped delay coordinates. CNS 2020: virtual.
Why is comparing neuro-computation in different species so important? Future frameworks of theoretical neuroscience 2019: University of Texas at San Antonio .
Dynamic neural field modeling of auditory categorization tasks. CNS 2019: Barcelona, Spain.
Diffusion Maps and their application to auditory streaming of triplets. RTG parameter estimation workshop 2018: North Carolina State University.
Invited talks
Adding Spikes in the FitzHugh-Nagumo Model with Low-Frequency Periodic Forcing. SIAM-LS. Portland, OR.
Artificial and biological neural networks: Using data to inform dynamic models. Computational Science Seminar. UT Dallas.
Extracting intrinsic neural features of bistable perception with the extended DMD.
SIAM-LS. (2022)
Incorporating data when equations are not enough. Weber State University. (2022)
Discovering neural features of auditory bistable perception from human electrocorticography data. Mathematics colloquium series: Southern Methodist University. (2021)
Contributed talks
Automatic differentiation and differentiable programming: Expanding deep learning architectures. Math Bio seminar: The University of Iowa. (2019)
Online machine learning enhanced artificial viscosity to suppress spurious oscillations near shocks in a staggered-grid Lagrangian scheme. Los Alamos National Laboratory: Los Alamos, NM. (2019)
Should I wear a coat outside? Decision making in a changing environment. (Chalk-talk) GAUSS Seminar: The University of Iowa. (2019)
Auditory categorization: A dynamic field approach. Math Bio seminar: The University of Iowa. (2018)
An introduction the the Kalman filter. Math Bio Seminar: The University of Iowa. (2018)
Dualing objectives. Applied Student Seminar: The University of Iowa. (2017)