activity
20242026
most citedKolmogorov-Arnold Networks (KANs) for Time Series Analysis

119 citations · 120 across the 6 of their papers we have counts for

collaborators

7 papers

eess.SP2026

Goal-oriented probabilistic forecasting for dynamic PRB allocation in 5G networks

Oier Larumbe-Lizarraga, Roberto Pereira, Cristian J. Vaca-Rubio

Efficient physical resource block (PRB) allocation in 5G networks requires accurate demand forecasting. Conventional methods minimize symmetric error metrics (MAE, RMSE), ignoring…

cs.LG2025

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…

eess.SP2025

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…

cs.NI2025

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…

cs.LG2024★ 1 cited

Learn More by Using Less: Distributed Learning with Energy-Constrained Devices

Roberto Pereira, Cristian J. Vaca-Rubio, Luis Blanco

Federated Learning (FL) has emerged as a solution for distributed model training across decentralized, privacy-preserving devices, but the different energy capacities of participat…

cs.LG2024

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…

eess.SP2024★ 119 cited

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…