Browsing Department of Computational and Data Sciences (CDS) by Subject "Initial conditions"
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Learning Multiple Initial Conditions using Physics Informed Neural Networks
Physics-Informed Neural Networks (PINNs) and its variants have emerged as a tool for solving differential equations in the past few years. Although several variants of PINNs have been proposed, the majority of these ...