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08/09/2023
Eigenvector Dreaming
Among the performance-enhancing procedures for Hopfield-type networks th...
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07/31/2023
The Decimation Scheme for Symmetric Matrix Factorization
Matrix factorization is an inference problem that has acquired importanc...
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06/28/2023
Sparse Representations, Inference and Learning
In recent years statistical physics has proven to be a valuable tool to ...
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04/28/2023
The Exponential Capacity of Dense Associative Memories
Recent generalizations of the Hopfield model of associative memories are...
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12/05/2022
Matrix factorization with neural networks
Matrix factorization is an important mathematical problem encountered in...
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10/17/2021
Perturbative construction of mean-field equations in extensive-rank matrix factorization and denoising
Factorization of matrices where the rank of the two factors diverges lin...
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02/16/2021
Capturing the learning curves of generic features maps for realistic data sets with a teacher-student model
Teacher-student models provide a powerful framework in which the typical...
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09/20/2020
Epidemic mitigation by statistical inference from contact tracing data
Contact-tracing is an essential tool in order to mitigate the impact of ...
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06/25/2020
The Gaussian equivalence of generative models for learning with two-layer neural networks
Understanding the impact of data structure on learning in neural network...
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02/21/2020
Generalisation error in learning with random features and the hidden manifold model
We study generalised linear regression and classification for a syntheti...
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09/25/2019
Modelling the influence of data structure on learning in neural networks
The lack of crisp mathematical models that capture the structure of real...
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06/20/2019
High-temperature Expansions and Message Passing Algorithms
Improved mean-field technics are a central theme of statistical physics ...
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01/24/2017
Multi-Layer Generalized Linear Estimation
We consider the problem of reconstructing a signal from multi-layered (p...
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02/06/2014