Abstract: The existence and uniqueness of solutions of nonlinear fractional differential equations is the key point for stability theory and the design of feedback stabilization controllers. In this ...

This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis physics-informed neural networks (FBPINNs). To improve the ...

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ABSTRACT: This work predicts theoretically the phase portrait including the existence and uniqueness of ω-limit cycle for an initial value problem y( 0 )= y 0 with an ordinary differential equation y ...

Abstract: Over the years, analysis of Singularly Boundary Value Problems have been achieved by applying various methods and or techniques. Fundamental issues have been on the existence and uniqueness ...

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Department of Mathematical Statistics and Differential Equations, Ivan Franko National University of Lviv, Lviv, Ukraine Problems without initial conditions for evolution equations and variational ...

This paper presents In-Context Operator Networks (ICON), a neural network approach that can learn new operators from prompted data during the inference stage without requiring any weight updates.

Last year, MIT developed an AI/ML algorithm capable of learning and adapting to new information while on the job, not just during its initial training phase. These “liquid” neural networks (in the ...

Almost every biomedical systems analysis requires early decisions regarding the choice of the most suitable representations to be used. De facto the most prevalent choice is a system of ordinary ...