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Found 7 papers, 0 papers with code
Uncertainty quantification of receptor ligand binding sites prediction
Recent advancements in protein docking site prediction have highlighted the limitations of traditional rigid docking algorithms, like PIPER, which often neglect critical stochastic elements such as solvent-induced fluctuations.
Feature Network Methods in Machine Learning and Applications
This network representation allows us to view feature vectors as functions on the network.
Stochastic Functional Analysis and Multilevel Vector Field Anomaly Detection
An optimal vector field Karhunen-Loeve expansion is applied to such random field data.
Multilevel Stochastic Optimization for Imputation in Massive Medical Data Records
A potentially critical predicate for application of machine learning methods to datasets involves addressing this problem.
Multilevel orthogonal Bochner function subspaces with applications to robust machine learning
To uncover the separation between these classes, we employ the Karhunen-Loeve expansion and construct the appropriate subspaces.
Change Detection: A functional analysis perspective
We develop a new approach for detecting changes in the behavior of stochastic processes and random fields based on tensor product representations such as the Karhunen-Lo\`{e}ve expansion.
Probability Functional Analysis Statistics Theory Statistics Theory
Feature vector regularization in machine learning
Such feature vector regularization inherits a property from function denoising on ${\bf R}^n$, in that accuracy is non-monotonic in the denoising (regularization) parameter $\alpha$.
