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Luca Biggio
Luca Biggio
Research fellow, EPFL
Verifisert e-postadresse på epfl.ch
Tittel
Sitert av
Sitert av
År
Neural Symbolic Regression that Scales
L Biggio, T Bendinelli, A Neitz, A Lucchi, G Parascandolo
International Conference on Machine Learning (ICML) 2021, 2021
2052021
Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial
V Nemani, L Biggio, X Huan, Z Hu, O Fink, A Tran, Y Wang, X Zhang, ...
Mechanical Systems and Signal Processing 205, 110796, 2023
1112023
Prognostics and health management of industrial assets: Current progress and road ahead
L Biggio, I Kastanis
Frontiers in Artificial Intelligence 3, 578613, 2020
1052020
Signal Propagation in Transformers: Theoretical Perspectives and the Role of Rank Collapse
L Noci, S Anagnostidis, L Biggio, A Orvieto, SP Singh, A Lucchi
Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), 2022
782022
FIGARO: Controllable music generation using learned and expert features
D von Rütte, L Biggio, Y Kilcher, T Hofmann
The Eleventh International Conference on Learning Representations, 2023
70*2023
Uncertainty-aware prognosis via deep gaussian process
L Biggio, A Wieland, MA Chao, I Kastanis, O Fink
IEEE Access 9, 123517-123527, 2021
61*2021
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
S Anagnostidis, D Pavllo, L Biggio, L Noci, A Lucchi, T Hoffmann
NeurIPS 2023 (spotlight), 2023
552023
Ageing-aware battery discharge prediction with deep learning
L Biggio, T Bendinelli, C Kulkarni, O Fink
Applied Energy 346, 121229, 2023
36*2023
On the effectiveness of randomized signatures as reservoir for learning rough dynamics
EM Compagnoni, A Scampicchio, L Biggio, A Orvieto, T Hofmann, ...
2023 International Joint Conference on Neural Networks (IJCNN), 1-8, 2023
25*2023
An sde for modeling sam: Theory and insights
EM Compagnoni, L Biggio, A Orvieto, FN Proske, H Kersting, A Lucchi
International Conference on Machine Learning, 25209-25253, 2023
242023
A seq2seq approach to symbolic regression
L Biggio, T Bendinelli, A Lucchi, G Parascandolo
Learning Meets Combinatorial Algorithms at NeurIPS2020, 2020
192020
Controllable neural symbolic regression
T Bendinelli, L Biggio, PA Kamienny
International Conference on Machine Learning, 2063-2077, 2023
172023
Prognostics and health management of industrial assets: Current progress and road ahead. Front
L Biggio, I Kastanis
Artif. Intell 3 (578613), 10.3389, 2020
172020
Fast emulation of two-point angular statistics for photometric galaxy surveys
M Bonici, L Biggio, C Carbone, L Guzzo
Monthly Notices of the Royal Astronomical Society 531 (4), 4203-4211, 2024
92024
Phme data challenge 2021
L Biggio, M Russi, S Bigdeli, I Kastanis, D Giordano, D Gagar
7th European Conference of the PHM Society, 2021
8*2021
Modeling lens potentials with continuous neural fields in galaxy-scale strong lenses
L Biggio, G Vernardos, A Galan, A Peel
arXiv preprint arXiv:2210.09169, 2022
72022
GEMTELLIGENCE: Accelerating gemstone classification with deep learning
T Bendinelli, L Biggio, D Nyfeler, A Ghosh, P Tollan, MA Kirschmann, ...
Communications Engineering 3 (1), 110, 2024
52024
Harnessing synthetic datasets: The role of shape bias in deep neural network generalization
E Benarous, S Anagnostidis, L Biggio, T Hofmann
arXiv preprint arXiv:2311.06224, 2023
52023
Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematic analyses
MR Gomer, S Ertl, L Biggio, H Wang, A Galan, L Van de Vyvere, D Sluse, ...
Astronomy & Astrophysics 679, A59, 2023
5*2023
Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers
F Behrens, L Biggio, L Zdeborová
arXiv preprint arXiv:2407.11542, 2024
2*2024
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Artikler 1–20