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Luca Biggio
Luca Biggio
Research fellow, EPFL
Verified email at epfl.ch
Title
Cited by
Cited by
Year
Neural Symbolic Regression that Scales
L Biggio, T Bendinelli, A Neitz, A Lucchi, G Parascandolo
International Conference on Machine Learning (ICML) 2021, 2021
1642021
Prognostics and health management of industrial assets: Current progress and road ahead
L Biggio, I Kastanis
Frontiers in Artificial Intelligence 3, 578613, 2020
992020
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
632023
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
55*2023
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
462022
Uncertainty-aware prognosis via deep gaussian process
L Biggio, A Wieland, MA Chao, I Kastanis, O Fink
Ieee Access 9, 123517-123527, 2021
46*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
302023
Ageing-aware battery discharge prediction with deep learning
L Biggio, T Bendinelli, C Kulkarni, O Fink
Applied Energy 346, 121229, 2023
26*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
18*2023
A seq2seq approach to symbolic regression
L Biggio, T Bendinelli, A Lucchi, G Parascandolo
Learning Meets Combinatorial Algorithms at NeurIPS2020, 2020
172020
An SDE for Modeling SAM: Theory and Insights
E Monzio Compagnoni, L Biggio, A Orvieto, FN Proske, H Kersting, ...
arXiv e-prints, arXiv: 2301.08203, 2023
15*2023
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
Controllable neural symbolic regression
T Bendinelli, L Biggio, PA Kamienny
International Conference on Machine Learning, 2063-2077, 2023
72023
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
62024
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
52022
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
4*2023
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
32023
Time delay estimation in unresolved lensed quasars
L Biggio, A Domi, S Tosi, G Vernardos, D Ricci, L Paganin, G Bracco
Monthly Notices of the Royal Astronomical Society, 2022
22022
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
12024
Understanding counting in small transformers: The interplay between attention and feed-forward layers
F Behrens, L Biggio, L Zdeborová
arXiv preprint arXiv:2407.11542, 2024
12024
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Articles 1–20