7 papers · 1 filter
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…
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…
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…