Alessandro Favero

About Alessandro Favero

Alessandro Favero, With an exceptional h-index of 4 and a recent h-index of 4 (since 2020), a distinguished researcher at École Polytechnique Fédérale de Lausanne, specializes in the field of Deep Learning, Machine Learning, Statistical Physics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models

Multi-Modal Hallucination Control by Visual Information Grounding

A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model

Statistical Mechanics of Infinitely-Wide Convolutional Networks

What Can Be Learnt With Wide Convolutional Neural Networks?

Diffeomorphisms invariance is a proxy of performance in deep neural networks

Locality defeats the curse of dimensionality in convolutional teacher-student scenarios

Alessandro Favero Information

University

Position

___

Citations(all)

50

Citations(since 2020)

50

Cited By

0

hIndex(all)

4

hIndex(since 2020)

4

i10Index(all)

3

i10Index(since 2020)

3

Email

University Profile Page

École Polytechnique Fédérale de Lausanne

Google Scholar

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Alessandro Favero Skills & Research Interests

Deep Learning

Machine Learning

Statistical Physics

Top articles of Alessandro Favero

Title

Journal

Author(s)

Publication Date

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models

Guillermo Ortiz-Jimenez*

Alessandro Favero*

Pascal Frossard

2023/5/22

Multi-Modal Hallucination Control by Visual Information Grounding

arXiv preprint arXiv:2403.14003

Alessandro Favero

Luca Zancato

Matthew Trager

Siddharth Choudhary

Pramuditha Perera

...

2024/3/20

A Phase Transition in Diffusion Models Reveals the Hierarchical Nature of Data

arXiv preprint arXiv:2402.16991

Antonio Sclocchi

Alessandro Favero

Matthieu Wyart

2024/2/26

How Deep Neural Networks Learn Compositional Data: The Random Hierarchy Model

arXiv e-prints

Francesco Cagnetta

Leonardo Petrini

Umberto M Tomasini

Alessandro Favero

Matthieu Wyart

2023/7

Statistical Mechanics of Infinitely-Wide Convolutional Networks

Bulletin of the American Physical Society

Alessandro Favero

Francesco Cagnetta

Matthieu Wyart

2023/3/6

What Can Be Learnt With Wide Convolutional Neural Networks?

International Conference on Machine Learning, 2023

Francesco Cagnetta

Alessandro Favero

Matthieu Wyart

2022/8/1

Diffeomorphisms invariance is a proxy of performance in deep neural networks

APS March Meeting Abstracts

Leonardo Petrini

Alessandro Favero

Mario Geiger

Matthieu Wyart

2023

Locality defeats the curse of dimensionality in convolutional teacher-student scenarios

Advances in Neural Information Processing Systems

Alessandro Favero

Francesco Cagnetta

Matthieu Wyart

2021/12/6

Spectral analysis of infinitely wide convolutional neural networks

Alessandro Favero

2020/10/23

See List of Professors in Alessandro Favero University(École Polytechnique Fédérale de Lausanne)

Co-Authors

H-index: 66
Pascal Frossard

Pascal Frossard

École Polytechnique Fédérale de Lausanne

H-index: 19
Mario Geiger

Mario Geiger

École Polytechnique Fédérale de Lausanne

H-index: 11
Guillermo Ortiz-Jiménez

Guillermo Ortiz-Jiménez

École Polytechnique Fédérale de Lausanne

H-index: 8
Francesco Cagnetta

Francesco Cagnetta

École Polytechnique Fédérale de Lausanne

H-index: 4
Leonardo Petrini

Leonardo Petrini

École Polytechnique Fédérale de Lausanne

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