87 citations · 544 across the 27 of their papers we have counts for
28 papers
Mostly-monocular responses and other visual functions in a multiscale network model of Macaque V1
Zhuo-Cheng Xiao, Kevin K. Lin, Lai-Sang Young
Visual signals from the two eyes merge gradually as they pass through the primary visual cortex (V1). Here we use a computational model of Macaque V1 to study the first stage of th…
Numerical analysis for leaky-integrate-fire networks under Euler-Maruyama
Xu'an Dou, Frank Chen, Kevin K Lin +1
Leaky integrate-and-fire (LIF) networks are standard reduced models for spike-based neural dynamics and a natural substrate for neuromorphic computation. We study time-driven Euler…
Numerical study of high-dimensional covariance estimation and localization for data assimilation
Shay Gilpin, Matthias Morzfeld, Kevin K. Lin
Covariance localization is a critical component of ensemble-based data assimilation (DA) and many current localization schemes simply dampen correlations as a function of distance.…
A data-informed mean-field approach to mapping of cortical parameter landscapes
Zhuo-Cheng Xiao, Kevin K. Lin, Lai-Sang Young
Constraining the many biological parameters that govern cortical dynamics is computationally and conceptually difficult because of the curse of dimensionality. This paper addresses…
Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism
Kevin K. Lin, Fei Lu
Model reduction methods aim to describe complex dynamic phenomena using only relevant dynamical variables, decreasing computational cost, and potentially highlighting key dynamical…
Symmetrized importance samplers for stochastic differential equations
Andrew Leach, Kevin K. Lin, Matthias Morzfeld
We study a class of importance sampling methods for stochastic differential equations (SDEs). A small-noise analysis is performed, and the results suggest that a simple symmetrizat…