works on

From the 1 of 8 linked papers with an AI index.

most cited5G Configured Grant Scheduling for 5G-TSN Integration for the Support of Industry 4.0

24 citations · 54 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2026

An Introduction to Sparse Identification of Nonlinear Dynamics for Engineering Applications

Yao Cheng Li, Ana Larrañaga, Steven L. Brunton +1

The paper presents a tutorial on the Sparse Identification of Nonlinear Dynamics (SINDy) method, showing how sparse regression can uncover interpretable governing equations from sm…

cs.NI202624 cited

5G Configured Grant Scheduling for 5G-TSN Integration for the Support of Industry 4.0

Ana Larrañaga, M. Carmen Lucas-Estañ, Imanol Martinez +1

Factories are evolving towards digitalized data-based ecosystems under the paradigm of the Industry 4.0 where new industrial services allow the implementation of more robust, resil…

quant-ph2026

Active Learning for Calibrating Entangling Gates via Surrogate-Based Optimization

Caleb Walton, Patricia García-Caspueñas, Filippo Zacchei +3

The fidelity of a quantum gate is sensitive to small deviations in the physical control parameters. Unfortunately, it is generally difficult to exactly model the implemented Hamilt…

cs.NI20268 cited

Configured Grant Scheduling for the Support of TSN Traffic in 5G and Beyond Industrial Networks

M. Carmen Lucas-Estañ, Ana Larrañaga, Javier Gozalvez +1

5G and beyond networks can facilitate the digital transformation of manufacturing and support more flexible and reconfigurable factories with ubiquitous mobile connectivity. This r…

cs.NI202622 cited

An open-source implementation and validation of 5G NR Configured Grant for URLLC in ns-3 5G LENA: a scheduling case study in Industry 4.0 scenarios

Ana Larrañaga, M. Carmen Lucas-Estañ, Sandra Lagén +3

Factories are undergoing a digital transformation towards cost-efficient, zero-defect manufacturing, creating the need for communication networks capable of meeting stringent laten…

cs.LG2026

Multi-Fidelity SINDy: Sparse Discovery of Nonlinear Dynamical Systems with Fidelity-Weighted Measurements

Filippo Zacchei, Ana Larrañaga, Attilio Frangi +2

Data from simulations and experiments are rarely noise-free and often exhibit heterogeneous levels of fidelity. Measurement uncertainty may vary across repeated observations, sensi…