119 citations · 119 across the 6 of their papers we have counts for
6 papers
A Primer on Kolmogorov-Arnold Networks (KANs) for Probabilistic Time Series Forecasting
Cristian J. Vaca-Rubio, Roberto Pereira, Luis Blanco +2
This work introduces Probabilistic Kolmogorov-Arnold Network (P-KAN), a novel probabilistic extension of Kolmogorov-Arnold Networks (KANs) for time series forecasting. By replacing…
On the Architectural Split and Radio Intelligence Controller Placement in Integrated O-RAN-enabled Non-Terrestrial Networks
Jorge Baranda, Marius Caus, Luis Blanco +5
The integration of Terrestrial Networks (TNs) with Non-Terrestrial Networks (NTNs) poses unique architectural and functional challenges due to heterogeneous propagation conditions,…
Probabilistic Forecasting for Network Resource Analysis in Integrated Terrestrial and Non-Terrestrial Networks
Cristian J. Vaca-Rubio, Vaishnavi Kasuluru, Engin Zeydan +4
Efficient resource management is critical for Non-Terrestrial Networks (NTNs) to provide consistent, high-quality service in remote and under-served regions. While traditional sing…
Fed-KAN: Federated Learning with Kolmogorov-Arnold Networks for Traffic Prediction
Engin Zeydan, Cristian J. Vaca-Rubio, Luis Blanco +3
Non-Terrestrial Networks (NTNs) are becoming a critical component of modern communication infrastructures, especially with the advent of Low Earth Orbit (LEO) satellite systems. Tr…
F-KANs: Federated Kolmogorov-Arnold Networks
Engin Zeydan, Cristian J. Vaca-Rubio, Luis Blanco +3
In this paper, we present an innovative federated learning (FL) approach that utilizes Kolmogorov-Arnold Networks (KANs) for classification tasks. By utilizing the adaptive activat…
Kolmogorov-Arnold Networks (KANs) for Time Series Analysis
Cristian J. Vaca-Rubio, Luis Blanco, Roberto Pereira +1
This paper introduces a novel application of Kolmogorov-Arnold Networks (KANs) to time series forecasting, leveraging their adaptive activation functions for enhanced predictive mo…