Elies Gil-Fuster

According to our database, Elies Gil-Fuster authored at least 16 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

Optimal algorithmic complexity of inference in quantum kernel methods.

Elies Gil-Fuster, Seongwook Shin, Sofiène Jerbi, Jens Eisert, Maximilian J. Kramer

CoRR, April, 2026

A PAC-Bayesian approach to generalization for quantum models.

Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert, Elies Gil-Fuster, Franz J. Schreiber, Carlos Bravo-Prieto

CoRR, March, 2026

2025

Prospects for quantum advantage in machine learning from the representability of functions.

Sergi Masot-Llima, Elies Gil-Fuster, Carlos Bravo-Prieto, Jens Eisert, Tommaso Guaita

CoRR, December, 2025

Quantum computing and artificial intelligence: status and perspectives.

Giovanni Acampora, Andris Ambainis, Natalia Ares, Leonardo Banchi, Pallavi Bhardwaj, Daniele Binosi, G. Andrew D. Briggs, Tommaso Calarco, Vedran Dunjko, Jens Eisert, Olivier Ezratty, Paul Erker, Federico Fedele, Elies Gil-Fuster, Martin Gärttner, Mats Granath, Markus Heyl, Iordanis Kerenidis, Matthias Klusch, Anton Frisk Kockum, Richard Kueng, Mario Krenn, Jörg Lässig, Antonio Macaluso, Sabrina Maniscalco, Florian Marquardt, Kristel Michielsen, Gorka Muñoz-Gil, Daniel Müssig, Hendrik Poulsen Nautrup, Evert P. L. van Nieuwenburg, Roman Orus, Jörg Schmiedmayer, Markus Schmitt, Philipp Slusallek, Filippo Vicentini, Christof Weitenberg, Frank K. Wilhelm

CoRR, May, 2025

Double descent in quantum machine learning.

Marie C. Kempkes, Aroosa Ijaz, Elies Gil-Fuster, Carlos Bravo-Prieto, Jakob Spiegelberg, Evert P. L. van Nieuwenburg, Vedran Dunjko

CoRR, January, 2025

Potential and limitations of random Fourier features for dequantizing quantum machine learning.

Ryan Sweke, Erik Recio-Armengol, Sofiène Jerbi, Elies Gil-Fuster, Bryce Fuller, Jens Eisert, Johannes Jakob Meyer

Quantum, 2025

On the Relation between Trainability and Dequantization of Variational Quantum Learning Models.

Elies Gil-Fuster, Casper Gyurik, Adrián Pérez-Salinas, Vedran Dunjko

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

On the expressivity of embedding quantum kernels.

Elies Gil-Fuster, Jens Eisert, Vedran Dunjko

Mach. Learn. Sci. Technol., 2024

Opportunities and limitations of explaining quantum machine learning.

Elies Gil-Fuster, Jonas R. Naujoks, Grégoire Montavon, Thomas Wiegand, Wojciech Samek, Jens Eisert

CoRR, 2024

Concept learning of parameterized quantum models from limited measurements.

Beng Yee Gan, Po-Wei Huang, Elies Gil-Fuster, Patrick Rebentrost

CoRR, 2024

2023

Potential and limitations of random Fourier features for dequantizing quantum machine learning.

Ryan Sweke, Erik Recio, Sofiène Jerbi, Elies Gil-Fuster, Bryce Fuller, Jens Eisert, Johannes Jakob Meyer

CoRR, 2023

Understanding quantum machine learning also requires rethinking generalization.

Elies Gil-Fuster, Jens Eisert, Carlos Bravo-Prieto

CoRR, 2023

2022

Exploiting symmetry in variational quantum machine learning.

Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster, Antonio Anna Mele, Francesco Arzani, Alissa Wilms, Jens Eisert

CoRR, 2022

2021

Encoding-dependent generalization bounds for parametrized quantum circuits.

Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, Ryan Sweke

Quantum, 2021

Training Quantum Embedding Kernels on Near-Term Quantum Computers.

Thomas Hubregtsen, David Wierichs, Elies Gil-Fuster, Peter-Jan H. S. Derks, Paul K. Fährmann, Johannes Jakob Meyer

CoRR, 2021

2020

Data re-uploading for a universal quantum classifier.

Adrián Pérez-Salinas, Alba Cervera-Lierta, Elies Gil-Fuster, José I. Latorre

Quantum, 2020