A new approach to the numerical solution of Fredholm integral equations using least squares-support vector regression. - K. Parand 001; Alireza Afzal Aghaei; Mostafa Jani; Ali Ghodsi 001 (Math. Comput. Simul., 2021)

Hyperparameter optimization of orthogonal functions in the numerical solution of differential equations. - Alireza Afzal Aghaei; Kourosh Parand (CoRR, 2023)

Solving Falkner-Skan type equations via Legendre and Chebyshev Neural Blocks. - Alireza Afzal Aghaei; Kourosh Parand; Ali Nikkhah; Shakila Jaberi (CoRR, 2023)

deepFDEnet: A Novel Neural Network Architecture for Solving Fractional Differential Equations. - Ali Nosrati Firoozsalari; Hassan Dana Mazraeh; Alireza Afzal Aghaei; Kourosh Parand (CoRR, 2023)

Automated assessment of the smoothness of retinal layers in optical coherence tomography images using a machine learning algorithm. - Jamshid Saeidian; Tahereh Mahmoudi; Hamid Riazi-Esfahani; Zahra Montazeriani; Alireza Khodabande; Mohammad Zarei; Nazanin Ebrahimiadib; Behzad Jafari; Alireza Afzal Aghaei; Hossein Azimi; Elias Khalili Pour (BMC Medical Imaging, 2023)

Accelerating Fractional PINNs using Operational Matrices of Derivative. - Tayebeh Taheri; Alireza Afzal Aghaei; Kourosh Parand (CoRR, 2024)

An Orthogonal Polynomial Kernel-Based Machine Learning Model for Differential-Algebraic Equations. - Tayebeh Taheri; Alireza Afzal Aghaei; Kourosh Parand (CoRR, 2024)

rKAN: Rational Kolmogorov-Arnold Networks. - Alireza Afzal Aghaei (CoRR, 2024)

PINNIES: An Efficient Physics-Informed Neural Network Framework to Integral Operator Problems. - Alireza Afzal Aghaei; Mahdi Movahedian Moghaddam; Kourosh Parand (CoRR, 2024)

A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations. - Alireza Afzal Aghaei (CoRR, 2024)

KANtrol: A Physics-Informed Kolmogorov-Arnold Network Framework for Solving Multi-Dimensional and Fractional Optimal Control Problems. - Alireza Afzal Aghaei (CoRR, 2024)

Solving a class of Thomas-Fermi equations: A new solution concept based on physics-informed machine learning. - Maryam Babaei; Alireza Afzal Aghaei; Zahra Kazemi; Mahdieh Jamshidi; Reza Ghaderi; Kourosh Parand (Math. Comput. Simul., 2024)

A neural network approach for solving nonlinear differential equations of Lane-Emden type. - K. Parand 001; Alireza Afzal Aghaei; S. Kiani; T. Ilkhas Zadeh; Z. Khosravi (Eng. Comput., 2024)

A machine learning framework for efficiently solving Fokker-Planck equations. - Ali Nosrati Firoozsalari; Alireza Afzal Aghaei; Kourosh Parand (Comput. Appl. Math., 2024)

Bridging machine learning and weighted residual methods for delay differential equations of fractional order. - Tayebeh Taheri; Alireza Afzal Aghaei; Kourosh Parand (Appl. Soft Comput., 2024)

The periodic Sinc kernel: Theoretical design and applications in machine learning and scientific computing. - Alireza Afzal Aghaei (Appl. Soft Comput., 2025)

fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions. - Alireza Afzal Aghaei (Neurocomputing, 2025)

TabKAN: Advancing Tabular Data Analysis using Kolmograv-Arnold Network. - Ali Eslamian; Alireza Afzal Aghaei; Qiang Cheng (CoRR, 2025)

A new kernel-based approach for solving general fractional (integro)-differential-algebraic equations. - Tayebeh Taheri; Alireza Afzal Aghaei; Kourosh Parand (Eng. Comput., 2025)

Personalized Control for Lower Limb Prosthesis Using Kolmogorov-Arnold Networks. - Seyed Mojtaba Mohasel; Alireza Afzal Aghaei; Corey A. Pew (CoRR, 2025)

A new Chebyshev operational matrix formulation of least-squares support vector regression for solving fractional integro-differential equations. - Alireza Afzal Aghaei; Armin Ghasem Nejad; Sohrabali Yousefi; Kourosh Parand (J. Comput. Appl. Math., 2026)