2.4k citations · 2.6k across the 6 of their papers we have counts for
6 papers
Augmented neural forms with parametric boundary-matching operators for solving ordinary differential equations
Adam D. Kypriadis, Isaac E. Lagaris, Aristidis Likas +1
Approximating solutions of ordinary and partial differential equations constitutes a significant challenge. Based on functional expressions that inherently depend on neural network…
Eliminating Multicollinearity Issues in Neural Network Ensembles: Incremental, Negatively Correlated, Optimal Convex Blending
Pola Lydia Lagari, Lefteri H. Tsoukalas, Salar Safarkhani +1
Given a {features, target} dataset, we introduce an incremental algorithm that constructs an aggregate regressor, using an ensemble of neural networks. It is well known that ensemb…
Neural Network Methods for Boundary Value Problems Defined in Arbitrarily Shaped Domains
I. E. Lagaris, A. Likas, D. G. Papageorgiou
Partial differential equations (PDEs) with Dirichlet boundary conditions defined on boundaries with simple geometry have been succesfuly treated using sigmoidal multilayer perceptr…
Training Reinforcement Neurocontrollers Using the Polytope Algorithm
A. Likas, I. E. Lagaris
A new training algorithm is presented for delayed reinforcement learning problems that does not assume the existence of a critic model and employs the polytope optimization algorit…
Artificial Neural Networks for Solving Ordinary and Partial Differential Equations
I. E. Lagaris, A. Likas, D. I. Fotiadis
We present a method to solve initial and boundary value problems using artificial neural networks. A trial solution of the differential equation is written as a sum of two parts. T…
Artificial Neural Network Methods in Quantum Mechanics
I. E. Lagaris, A. Likas, D. I. Fotiadis
In a previous article we have shown how one can employ Artificial Neural Networks (ANNs) in order to solve non-homogeneous ordinary and partial differential equations. In the prese…