16 citations · 37 across the 11 of their papers we have counts for
12 papers
Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
Armin Behnamnia, Gholamali Aminian, Alireza Aghaei +3
Off-policy learning and evaluation leverage logged bandit feedback datasets, which contain context, action, propensity score, and feedback for each data point. These scenarios face…
Personalized Control for Lower Limb Prosthesis Using Kolmogorov-Arnold Networks
SeyedMojtaba Mohasel, Alireza Afzal Aghaei, Corey Pew
Objective: This paper investigates the potential of learnable activation functions in Kolmogorov-Arnold Networks (KANs) for personalized control in a lower-limb prosthesis. In addi…
TabKAN: Advancing Tabular Data Analysis using Kolmogorov-Arnold Network
Ali Eslamian, Alireza Afzal Aghaei, Qiang Cheng
Tabular data analysis presents unique challenges that arise from heterogeneous feature types, missing values, and complex feature interactions. While traditional machine learning m…
KANtrol: A Physics-Informed Kolmogorov-Arnold Network Framework for Solving Multi-Dimensional and Fractional Optimal Control Problems
Alireza Afzal Aghaei
In this paper, we introduce the KANtrol framework, which utilizes Kolmogorov-Arnold Networks (KANs) to solve optimal control problems involving continuous time variables. We explai…
A Physics-Informed Machine Learning Approach for Solving Distributed Order Fractional Differential Equations
Alireza Afzal Aghaei
This paper introduces a novel methodology for solving distributed-order fractional differential equations using a physics-informed machine learning framework. The core of this appr…
PINNIES: An Efficient Physics-Informed Neural Network Framework to Integral Operator Problems
Alireza Afzal Aghaei, Mahdi Movahedian Moghaddam, Kourosh Parand
This paper introduces an efficient tensor-vector product technique for the rapid and accurate approximation of integral operators within physics-informed deep learning frameworks.…
rKAN: Rational Kolmogorov-Arnold Networks
Alireza Afzal Aghaei
The development of Kolmogorov-Arnold networks (KANs) marks a significant shift from traditional multi-layer perceptrons in deep learning. Initially, KANs employed B-spline curves a…
fKAN: Fractional Kolmogorov-Arnold Networks with trainable Jacobi basis functions
Alireza Afzal Aghaei
Recent advancements in neural network design have given rise to the development of Kolmogorov-Arnold Networks (KANs), which enhance speed, interpretability, and precision. This pap…
An Orthogonal Polynomial Kernel-Based Machine Learning Model for Differential-Algebraic Equations
Tayebeh Taheri, Alireza Afzal Aghaei, Kourosh Parand
The recent introduction of the Least-Squares Support Vector Regression (LS-SVR) algorithm for solving differential and integral equations has sparked interest. In this study, we ex…
Accelerating Fractional PINNs using Operational Matrices of Derivative
Tayebeh Taheri, Alireza Afzal Aghaei, Kourosh Parand
This paper presents a novel operational matrix method to accelerate the training of fractional Physics-Informed Neural Networks (fPINNs). Our approach involves a non-uniform discre…
deepFDEnet: A Novel Neural Network Architecture for Solving Fractional Differential Equations
Ali Nosrati Firoozsalari, Hassan Dana Mazraeh, Alireza Afzal Aghaei +1
The primary goal of this research is to propose a novel architecture for a deep neural network that can solve fractional differential equations accurately. A Gaussian integration r…
Solving Falkner-Skan type equations via Legendre and Chebyshev Neural Blocks
Alireza Afzal Aghaei, Kourosh Parand, Ali Nikkhah +1
In this paper, a new deep-learning architecture for solving the non-linear Falkner-Skan equation is proposed. Using Legendre and Chebyshev neural blocks, this approach shows how or…