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Improving Sampling and Function Approximation in Machine Learning Methods for Solving Partial Differential Equations
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Modified Functional Principal Component Regression
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Reinforcement Learning with Manifold Optimization
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Parameter Tuning for SIR-Related Models With Variational and Bayesian Methods
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Mathematical modeling and simulation of coronary stents
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Generalized Quantile Random Forest with Smoothed Estimating Equations
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Low Precision Preconditioning for Iterated Tikhonov Regularization
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Conditional Sampling and Density Estimation with Triangular Convex Flows
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Reducing Operator Complexity in Algebraic Multigrid with Machine Learning Approaches
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In-silico analysis of the novel Caenorhabditis elegans tropomyosin with poor actin affinity
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