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Alessandro Ingrosso
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2020 – today
- 2024
- [i9]Federico Bassetti, Marco Gherardi, Alessandro Ingrosso, Mauro Pastore, Pietro Rotondo:
Feature learning in finite-width Bayesian deep linear networks with multiple outputs and convolutional layers. CoRR abs/2406.03260 (2024) - 2023
- [c1]Maria Refinetti, Alessandro Ingrosso, Sebastian Goldt:
Neural networks trained with SGD learn distributions of increasing complexity. ICML 2023: 28843-28863 - [i8]Alessandro Ingrosso, Emanuele Panizon:
Machine learning at the mesoscale: a computation-dissipation bottleneck. CoRR abs/2307.02379 (2023) - 2022
- [j3]Rainer Engelken, Alessandro Ingrosso, Ramin Khajeh, Sven Goedeke, L. F. Abbott:
Input correlations impede suppression of chaos and learning in balanced firing-rate networks. PLoS Comput. Biol. 18(12): 1010590 (2022) - [i7]Rainer Engelken, Alessandro Ingrosso, Ramin Khajeh, Sven Goedeke, L. F. Abbott:
Input correlations impede suppression of chaos and learning in balanced rate networks. CoRR abs/2201.09916 (2022) - [i6]Maria Refinetti, Alessandro Ingrosso, Sebastian Goldt:
Neural networks trained with SGD learn distributions of increasing complexity. CoRR abs/2211.11567 (2022) - 2020
- [j2]Alessandro Ingrosso:
Optimal learning with excitatory and inhibitory synapses. PLoS Comput. Biol. 16(12) (2020) - [i5]Alessandro Ingrosso:
Optimal Learning with Excitatory and Inhibitory synapses. CoRR abs/2005.12330 (2020) - [i4]Antoine Baker, Indaco Biazzo, Alfredo Braunstein, Giovanni Catania, Luca Dall'Asta, Alessandro Ingrosso, Florent Krzakala, Fabio Mazza, Marc Mézard, Anna Paola Muntoni, Maria Refinetti, Stefano Sarao Mannelli, Lenka Zdeborová:
Epidemic mitigation by statistical inference from contact tracing data. CoRR abs/2009.09422 (2020)
2010 – 2019
- 2018
- [i3]Alessandro Ingrosso, L. F. Abbott:
Training dynamically balanced excitatory-inhibitory networks. CoRR abs/1812.11424 (2018) - 2016
- [j1]Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina:
Unreasonable effectiveness of learning neural networks: From accessible states and robust ensembles to basic algorithmic schemes. Proc. Natl. Acad. Sci. USA 113(48): E7655-E7662 (2016) - [i2]Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Alessandro Ingrosso, Carlo Lucibello, Luca Saglietti, Riccardo Zecchina:
Unreasonable Effectiveness of Learning Neural Nets: Accessible States and Robust Ensembles. CoRR abs/1605.06444 (2016) - [i1]Alfredo Braunstein, Alessandro Ingrosso:
Network reconstruction from infection cascades. CoRR abs/1609.00432 (2016)
Coauthor Index
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