Luca Biggio
Luca Biggio
Phd student, ETH Zurich
Verified email at
Cited by
Cited by
Neural Symbolic Regression that Scales
L Biggio, T Bendinelli, A Neitz, A Lucchi, G Parascandolo
International Conference on Machine Learning (ICML) 2021, 2021
Prognostics and health management of industrial assets: Current progress and road ahead
L Biggio, I Kastanis
Frontiers in Artificial Intelligence 3, 578613, 2020
Uncertainty-aware prognosis via deep gaussian process
L Biggio, A Wieland, MA Chao, I Kastanis, O Fink
IEEE Access 9, 123517-123527, 2021
A seq2seq approach to symbolic regression
L Biggio, T Bendinelli, A Lucchi, G Parascandolo
Learning Meets Combinatorial Algorithms at NeurIPS2020, 2020
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
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
Phme data challenge 2021
L Biggio, M Russi, S Bigdeli, I Kastanis, D Giordano, D Gagar
7th European Conference of the PHM Society, 2021
Dynaformer: A Deep Learning Model for Ageing-aware Battery Discharge Prediction
L Biggio, T Bendinelli, C Kulkarni, O Fink
arXiv preprint arXiv:2206.02555, 2022
Fast emulation of two-point angular statistics for photometric galaxy surveys
M Bonici, L Biggio, C Carbone, L Guzzo
arXiv preprint arXiv:2206.14208, 2022
Randomized Signature Layers for Signal Extraction in Time Series Data
EM Compagnoni, L Biggio, A Orvieto, T Hofmann, J Teichmann
arXiv preprint arXiv:2201.00384, 2022
An SDE for Modeling SAM: Theory and Insights
E Monzio Compagnoni, A Orvieto, L Biggio, H Kersting, FN Proske, ...
arXiv e-prints, arXiv: 2301.08203, 2023
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
Dynamic Context Pruning for Efficient and Interpretable Autoregressive Transformers
S Anagnostidis, D Pavllo, L Biggio, L Noci, A Lucchi, T Hoffmann
arXiv preprint arXiv:2305.15805, 2023
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 Du, ...
arXiv preprint arXiv:2305.04933, 2023
Controllable Neural Symbolic Regression
T Bendinelli, L Biggio, PA Kamienny
arXiv preprint arXiv:2304.10336, 2023
Datenbasierte Instandhaltung darf nicht zum Glücksspiel werden
L Biggio, PAE Schmid, I Kastanis
Cosmology from Galaxy Redshift Surveys with PointNet
S Anagnostidis, A Thomsen, T Kacprzak, T Tröster, L Biggio, A Refregier, ...
arXiv preprint arXiv:2211.12346, 2022
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
Fast kinematics modeling for conjunction with lens image modeling
MR Gomer, L Biggio, S Ertl, H Wang, A Galan, L Van de Vyvere, D Sluse, ...
Machine Learning and the Physical Sciences, NeurIPS 2022 Workshop, 2022
Self-supervised pre-training on industrial time-series
L Biggio, I Kastanis
2021 8th Swiss Conference on Data Science (SDS), 56-57, 2021
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