Publications of F. Matos

Journal Article (9)

1.
Journal Article
Dominguez-Palacios, J.; Futatani, S.; Garcia-Munoz, M.; Jansen van Vuuren, A.; Viezzer, E.; Gonzalez-Martin, J.; Toscano-Jimenez, M.; Oyola, P.; Todo, Y.; Suzuki, Y. et al.: Effect of energetic ions on edge-localized modes in tokamak plasmas. Nature Physics 21, pp. 43 - 51 (2025)
2.
Journal Article
Zohm, H.; Alessi, E.; Angioni, C.; Arden, N.; Artigues, V.; Astrain, M.; Asunta, O.; Balden, M.; Bandaru, V.; Banon Navarro, A. et al.: Overview of ASDEX upgrade results in view of ITER and DEMO. Nuclear Fusion 64, 112001 (2024)
3.
Journal Article
Reimerdes, H.; Agostini, M.; Alessi, E.; Alberti, S.; Andrebe, Y.; Arnichand, H.; Balbin, J.; Bagnato, F.; Baquero-Ruiz, M.; Bernert, M. et al.: Overview of the TCV tokamak experimental programme. Nuclear Fusion 62, 042018 (2022)
4.
Journal Article
Stroth, U.; Aguiam, D.; Alessi, E.; Angioni, C.; Arden, N.; Arredondo Parra, R.; Artigues, V.; Asunta, O.; Balden, M.; Bandaru, V. et al.: Progress from ASDEX Upgrade experiments in preparing the physics basis of ITER operation and DEMO scenario development. Nuclear Fusion 62, 042006 (2022)
5.
Journal Article
Matos, F.; Menkovski, V.; Pau, A.; Marceca, G.; Jenko, F.; TCV Team: Plasma confinement mode classification using a sequence-to-sequence neural network with attention. Nuclear Fusion 61, 046019 (2021)
6.
Journal Article
Matos, F.; Menkovski, V.; Felici, F.; Pau, A.; Jenko, F.; TCV Team; EUROfusion MST1 Team: Classification of tokamak plasma confinement states with convolutional recurrent neural networks. Nuclear Fusion 60, 036022 (2020)
7.
Journal Article
Matos, F.; Svensson, J.; Pavone, A.; Odstrcil, T.; Jenko, F.: Deep learning for Gaussian process soft x-ray tomography model selection in the ASDEX Upgrade tokamak. Review of Scientific Instruments 91, 103501 (2020)
8.
Journal Article
Coda, S.; Agostini, M.; Albanese, R.; Alberti, S.; Alessi, E.; Allan, S.; Allcock, J.; Ambrosino, R.; Anand, H.; Andrebe, Y. et al.: Physics research on the TCV tokamak facility: from conventional to alternative scenarios and beyond. Nuclear Fusion 59, 112023 (2019)
9.
Journal Article
Labit, B.; Eich, T.; Harrer, G. F.; Wolfrum, E.; Bernert, M.; Dunne, M. G.; Frassinetti, L.; Hennequin, P.; Maurizio, R.; Merle, A. et al.: Dependence on plasma shape and plasma fueling for small edge-localized mode regimes in TCV and ASDEX Upgrade. Nuclear Fusion 59, 086020 (2019)

Meeting Abstract (1)

10.
Meeting Abstract
Matos, F.; Menkovski, V.; Felici, F.; Pau, A.; Jenko, F.; TCV Team; EUROfusion MST1 Team: Classification of tokamak plasma confinement states with convolutional recurrent neural networks. In: Verhandlungen der Deutschen Physikalischen Gesellschaft, (VI) 55 (1), P 21.4. DPG-Frühjahrstagung der Sektion Atome, Moleküle, Quantenoptik und Plasmen (SAMOP), Hannover, March 08, 2020 - March 13, 2020. DPG, Bad Honnef (submitted)

Talk (2)

11.
Talk
Matos, F.; Menkovski, V.; Felici, F.; Pau, A.; Jenko, F.; TCV Team; EUROfusion MST1 Team: Plasma State Classification and ELM detection using Convolutional Long Short-Term Memory Neural Networks. 2nd International Conference on Data Driven Plasma Science (ICDDPS), Marseille (submitted)
12.
Talk
Matos, F.; Svensson, J.; Pavone, A.; Odstrcil, T.; Jenko, F.; ASDEX Upgrade Team, Max Planck Institute for Plasma Physics, Max Planck Society: Deep Neural Networks for Gaussian Process Tomography at the ASDEX Upgrade Tokamak. 3rd International Conference on Data-Driven Plasma Science (ICDDPS-3), Virtual (submitted)

Poster (3)

13.
Poster
Marceca, G.; Pau, A.; Felici, F.; Sauter, O.; Vu, T.; Galperti, C.; Matos, F.; Menkovski, V.; TCV team; EUROfusion MST1 Team et al.: Real-time recognition of plasma confinements states in the TCV Tokamak and transfer learning using ML models. 47th EPS Conference on Plasma Physics, Virtual (2021)
14.
Poster
Matos, F.; Menkovski, V.; Felici, F.; Jenko, F.; TCV Team: Convolutional LSTMs for Plasma State Classification. DPG-Frühjahrstagung 2019 der Sektion Materie und Kosmos (SMuK), München (submitted)
15.
Poster
Matos, F.; Hendrich, F.; Jenko, F.; Odstrcil, T.: Deep Learning for Plasma Diagnostics. 82. Jahrestagung der DPG und DPG-Frühjahrstagung der Sektion AMOP, Erlangen (submitted)

Thesis - PhD (1)

16.
Thesis - PhD
Duarte Pinto de Almeida Matos, F.: Deep Learning for Tomography, State Classification and Event Detection in Nuclear Fusion Plasmas. Dissertation, 228 pp., Technische Universität München, München (2021)
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