Elies Gil-Fuster

18 papers A* 1Journal 17
YearRankTypeTitle / Venue / Authors
2026 J jnl
A PAC-Bayesian approach to generalization for quantum models.
CoRR
Pablo Rodriguez-Grasa, Matthias C. Caro, Jens Eisert, Elies Gil-Fuster, Franz J. Schreiber, Carlos Bravo-Prieto
2025 J jnl
Double descent in quantum machine learning.
CoRR
Marie C. Kempkes, Aroosa Ijaz, Elies Gil-Fuster, Carlos Bravo-Prieto, Jakob Spiegelberg, Evert P. L. van Nieuwenburg, Vedran Dunjko
2025 A* conf
On the Relation between Trainability and Dequantization of Variational Quantum Learning Models.
ICLR
Elies Gil-Fuster, Casper Gyurik, Adrián Pérez-Salinas, Vedran Dunjko
2025 J jnl
Potential and limitations of random Fourier features for dequantizing quantum machine learning.
Quantum
Ryan Sweke, Erik Recio-Armengol, Sofiène Jerbi, Elies Gil-Fuster, Bryce Fuller, Jens Eisert, Johannes Jakob Meyer
2025 J jnl
Prospects for quantum advantage in machine learning from the representability of functions.
CoRR
Sergi Masot-Llima, Elies Gil-Fuster, Carlos Bravo-Prieto, Jens Eisert, Tommaso Guaita
2025 J jnl
Quantum computing and artificial intelligence: status and perspectives.
CoRR
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
2024 J jnl
Concept learning of parameterized quantum models from limited measurements.
CoRR
Beng Yee Gan, Po-Wei Huang, Elies Gil-Fuster, Patrick Rebentrost
2024 J jnl
On the expressivity of embedding quantum kernels.
Mach. Learn. Sci. Technol.
Elies Gil-Fuster, Jens Eisert, Vedran Dunjko
2024 J jnl
On the relation between trainability and dequantization of variational quantum learning models.
CoRR
Elies Gil-Fuster, Casper Gyurik, Adrián Pérez-Salinas, Vedran Dunjko
2024 J jnl
Opportunities and limitations of explaining quantum machine learning.
CoRR
Elies Gil-Fuster, Jonas R. Naujoks, Grégoire Montavon, Thomas Wiegand, Wojciech Samek, Jens Eisert
2023 J jnl
On the expressivity of embedding quantum kernels.
CoRR
Elies Gil-Fuster, Jens Eisert, Vedran Dunjko
2023 J jnl
Potential and limitations of random Fourier features for dequantizing quantum machine learning.
CoRR
Ryan Sweke, Erik Recio, Sofiène Jerbi, Elies Gil-Fuster, Bryce Fuller, Jens Eisert, Johannes Jakob Meyer
2023 J jnl
Understanding quantum machine learning also requires rethinking generalization.
CoRR
Elies Gil-Fuster, Jens Eisert, Carlos Bravo-Prieto
2022 J jnl
Exploiting symmetry in variational quantum machine learning.
CoRR
Johannes Jakob Meyer, Marian Mularski, Elies Gil-Fuster, Antonio Anna Mele, Francesco Arzani, Alissa Wilms, Jens Eisert
2021 J jnl
Encoding-dependent generalization bounds for parametrized quantum circuits.
CoRR
Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, Ryan Sweke
2021 J jnl
Encoding-dependent generalization bounds for parametrized quantum circuits.
Quantum
Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, Ryan Sweke
2021 J jnl
Training Quantum Embedding Kernels on Near-Term Quantum Computers.
CoRR
Thomas Hubregtsen, David Wierichs, Elies Gil-Fuster, Peter-Jan H. S. Derks, Paul K. Fährmann, Johannes Jakob Meyer
2020 J jnl
Data re-uploading for a universal quantum classifier.
Quantum
Adrián Pérez-Salinas, Alba Cervera-Lierta, Elies Gil-Fuster, José I. Latorre