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A data-driven study of random graphs & social networks intended for the department of mathematics and statistics
A probabilistic framework for the empirical mode decomposition and applications to precipitation data
A review of some inverse scale space methods for image reconstruction
A study of interior point methods on the compressed sensing problem
A study on quantifying effective training of DLDMD
Analysis of globus pallidus local field potentials and electrocorticograms of patients diagnosed with Parkinson’s disease
Analyzing complex flows in Bose-Einstein condensates using data-driven methods
Approximations to the Lid-Driven Cavity Problem
Bifurcation analysis of coupled spin torque nano oscillators parallel array configuration
Bifurcations and dynamics of feedforward networks
Characterizing coherent structures in Bose-Einstein condensates: A DMD approach
Classifying major capsid proteins utilizing the random forest algorithm on an imbalanced training set
Collective response of networks of Colpitts oscillators coupled bidirectionally
Collective response of networks of Colpitts oscillators coupled unidirectionally
Comoving vortex configurations in a channel
Computational aspects of the material point method with applications in computer graphics
Computed Tomography and The Radon Transform
Critical velocity and nucleation of dark solitons In non-local nonlinear media
Deep learning assisted Hankel dynamic mode decomposition
Developing data-driven methods to investigate complex flows in Bose-Einstein condensates

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