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Found 7 papers, 3 papers with code
Estimating and Assessing Differential Equation Models with Time-Course Data
Overall, we believe MAGI is a useful method for the analysis of time-course data in the context of ODE models, which bypasses the need for any numerical integration.
A Comparative Study of Compartmental Models for COVID-19 Transmission in Ontario, Canada
The continued spread of the virus underlying COVID-19 has been spurred by the emergence of variants since the initial outbreak in December, 2019.
Conformational variability of loops in the SARS-CoV-2 spike protein
Loop modeling methods were then applied to the S protein loop targets, and the prediction accuracies discussed in relation to the characteristics of the conformational clusters identified.
Ellipse Detection and Localization with Applications to Knots in Sawn Lumber Images
Specific to the lumber application, we also propose an algorithm to correct any misalignment in the raw timber images during scanning, and contribute the first open-source lumber knot dataset by labeling the elliptical knots in the preprocessed images.
Inference of dynamic systems from noisy and sparse data via manifold-constrained Gaussian processes
MAGI uses a Gaussian process model over time-series data, explicitly conditioned on the manifold constraint that derivatives of the Gaussian process must satisfy the ODE system.
Methodology Dynamical Systems
A Comparison Study on Nonlinear Dimension Reduction Methods with Kernel Variations: Visualization, Optimization and Classification
Because of high dimensionality, correlation among covariates, and noise contained in data, dimension reduction (DR) techniques are often employed to the application of machine learning algorithms.
Where Does Haydn End and Mozart Begin? Composer Classification of String Quartets
Several of these proposed summary features are found to be important for distinguishing between Haydn and Mozart string quartets.
Applications
