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Federica Gerace
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2020 – today
- 2024
- [c4]Riccardo Rende, Federica Gerace, Alessandro Laio, Sebastian Goldt:
A distributional simplicity bias in the learning dynamics of transformers. NeurIPS 2024 - [c3]Eszter Székely, Lorenzo Bardone, Federica Gerace, Sebastian Goldt:
Learning from higher-order correlations, efficiently: hypothesis tests, random features, and neural networks. NeurIPS 2024 - [i10]Riccardo Rende, Federica Gerace, Alessandro Laio, Sebastian Goldt:
A distributional simplicity bias in the learning dynamics of transformers. CoRR abs/2410.19637 (2024) - 2023
- [i9]Federica Gerace, Diego Doimo, Stefano Sarao Mannelli, Luca Saglietti, Alessandro Laio:
Optimal transfer protocol by incremental layer defrosting. CoRR abs/2303.01429 (2023) - [i8]Riccardo Rende, Federica Gerace, Alessandro Laio, Sebastian Goldt:
Optimal inference of a generalised Potts model by single-layer transformers with factored attention. CoRR abs/2304.07235 (2023) - [i7]Eszter Székely, Lorenzo Bardone, Federica Gerace, Sebastian Goldt:
Learning from higher-order statistics, efficiently: hypothesis tests, random features, and neural networks. CoRR abs/2312.14922 (2023) - 2022
- [j1]Federica Gerace
, Luca Saglietti, Stefano Sarao Mannelli
, Andrew M. Saxe
, Lenka Zdeborová:
Probing transfer learning with a model of synthetic correlated datasets. Mach. Learn. Sci. Technol. 3(1): 15030 (2022) - [i6]Federica Gerace, Florent Krzakala
, Bruno Loureiro, Ludovic Stephan, Lenka Zdeborová:
Gaussian Universality of Linear Classifiers with Random Labels in High-Dimension. CoRR abs/2205.13303 (2022) - [i5]Stefano Sarao Mannelli, Federica Gerace, Negar Rostamzadeh, Luca Saglietti:
Inducing bias is simpler than you think. CoRR abs/2205.15935 (2022) - 2021
- [i4]Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew M. Saxe, Lenka Zdeborová:
Probing transfer learning with a model of synthetic correlated datasets. CoRR abs/2106.05418 (2021) - 2020
- [c2]George Stamatescu, Federica Gerace, Carlo Lucibello, Ian G. Fuss, Langford B. White:
Critical initialisation in continuous approximations of binary neural networks. ICLR 2020 - [c1]Federica Gerace, Bruno Loureiro, Florent Krzakala
, Marc Mézard, Lenka Zdeborová:
Generalisation error in learning with random features and the hidden manifold model. ICML 2020: 3452-3462 - [i3]Federica Gerace, Bruno Loureiro
, Florent Krzakala, Marc Mézard, Lenka Zdeborová:
Generalisation error in learning with random features and the hidden manifold model. CoRR abs/2002.09339 (2020)
2010 – 2019
- 2019
- [i2]George Stamatescu, Federica Gerace, Carlo Lucibello
, Ian G. Fuss, Langford B. White:
Signal propagation in continuous approximations of binary neural networks. CoRR abs/1902.00177 (2019) - 2018
- [b1]Federica Gerace:
Statistical physics of neural systems. Polytechnic University of Turin, Italy, 2018 - 2017
- [i1]Carlo Baldassi, Federica Gerace, Hilbert J. Kappen, Carlo Lucibello, Luca Saglietti, Enzo Tartaglione, Riccardo Zecchina:
On the role of synaptic stochasticity in training low-precision neural networks. CoRR abs/1710.09825 (2017)
Coauthor Index
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