Michael J. Shelley

Orcid: 0000-0002-4835-0339

Affiliations:
  • New York University, New York, NY, USA


According to our database1, Michael J. Shelley authored at least 27 papers between 1993 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Learning fast, accurate, and stable closures of a kinetic theory of an active fluid.
J. Comput. Phys., 2024

Inferring biological processes with intrinsic noise from cross-sectional data.
CoRR, 2024

2023
Interpretable neural architecture search and transfer learning for understanding CRISPR-Cas9 off-target enzymatic reactions.
Nat. Comput. Sci., 2023

Stochastic force inference via density estimation.
CoRR, 2023

Interpretable neural architecture search and transfer learning for understanding sequence dependent enzymatic reactions.
CoRR, 2023

2022
A fast Chebyshev method for the Bingham closure with application to active nematic suspensions.
J. Comput. Phys., 2022

2021
A stable and accurate scheme for solving the Stefan problem coupled with natural convection using the Immersed Boundary Smooth Extension method.
J. Comput. Phys., 2021

2020
A scalable computational platform for particulate Stokes suspensions.
J. Comput. Phys., 2020

2018
Directed Migration of Microscale Swimmers by an Array of Shaped Obstacles: Modeling and Shape Optimization.
SIAM J. Appl. Math., 2018

Universal image systems for non-periodic and periodic Stokes flows above a no-slip wall.
J. Comput. Phys., 2018

Flexibly imposing periodicity in kernel independent FMM: A multipole-to-local operator approach.
J. Comput. Phys., 2018

2017
A fast platform for simulating semi-flexible fiber suspensions applied to cell mechanics.
J. Comput. Phys., 2017

2012
Editorial.
Adv. Comput. Math., 2012

2011
Applying a second-kind boundary integral equation for surface tractions in Stokes flow.
J. Comput. Phys., 2011

2010
Shape optimization of peristaltic pumping.
J. Comput. Phys., 2010

Modeling simple locomotors in Stokes flow.
J. Comput. Phys., 2010

LFP spectral peaks in V1 cortex: network resonance and cortico-cortical feedback.
J. Comput. Neurosci., 2010

2009
A neuronal network model of primary visual cortex explains spatial frequency selectivity.
J. Comput. Neurosci., 2009

2008
Theoretical analysis of reverse-time correlation for idealized orientation tuning dynamics.
J. Comput. Neurosci., 2008

Retinal and cortical nonlinearities combine to produce masking in V1 responses to plaids.
J. Comput. Neurosci., 2008

2006
Moore's law and the Saffman-Taylor instability.
J. Comput. Phys., 2006

2002
States of High Conductance in a Large-Scale Model of the Visual Cortex .
J. Comput. Neurosci., 2002

Coarse-Grained Reduction and Analysis of a Network Model of Cortical Response: I. Drifting Grating Stimuli.
J. Comput. Neurosci., 2002

2001
Efficient and Accurate Time-Stepping Schemes for Integrate-and-Fire Neuronal Networks.
J. Comput. Neurosci., 2001

2000
Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex.
J. Comput. Neurosci., 2000

1993
High-Order and Efficient Methods for the Vorticity Formulation of the Euler Equations.
SIAM J. Sci. Comput., 1993

The Convergence of an Exact Desingularization for Vortex Methods.
SIAM J. Sci. Comput., 1993


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