ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2110.00683
  4. Cited By
Learning through atypical "phase transitions" in overparameterized
  neural networks
v1v2 (latest)

Learning through atypical "phase transitions" in overparameterized neural networks

1 October 2021
Carlo Baldassi
Clarissa Lauditi
Enrico M. Malatesta
R. Pacelli
Gabriele Perugini
R. Zecchina
ArXiv (abs)PDFHTML

Papers citing "Learning through atypical "phase transitions" in overparameterized neural networks"

16 / 16 papers shown
Title
High-dimensional manifold of solutions in neural networks: insights from statistical physics
High-dimensional manifold of solutions in neural networks: insights from statistical physics
Enrico M. Malatesta
114
4
0
20 Feb 2025
Exact full-RSB SAT/UNSAT transition in infinitely wide two-layer neural networks
Exact full-RSB SAT/UNSAT transition in infinitely wide two-layer neural networks
B. Annesi
Enrico M. Malatesta
Francesco Zamponi
92
3
0
09 Oct 2024
ClassiFIM: An Unsupervised Method To Detect Phase Transitions
ClassiFIM: An Unsupervised Method To Detect Phase Transitions
Victor Kasatkin
E. Mozgunov
Nicholas Ezzell
Utkarsh Mishra
Itay Hen
Daniel Lidar
80
3
0
06 Aug 2024
Random Features Hopfield Networks generalize retrieval to previously
  unseen examples
Random Features Hopfield Networks generalize retrieval to previously unseen examples
Silvio Kalaj
Clarissa Lauditi
Gabriele Perugini
Carlo Lucibello
Enrico M. Malatesta
Matteo Negri
AAML
76
9
0
08 Jul 2024
The twin peaks of learning neural networks
The twin peaks of learning neural networks
Elizaveta Demyanenko
Christoph Feinauer
Enrico M. Malatesta
Luca Saglietti
62
0
0
23 Jan 2024
Engineered Ordinary Differential Equations as Classification Algorithm
  (EODECA): thorough characterization and testing
Engineered Ordinary Differential Equations as Classification Algorithm (EODECA): thorough characterization and testing
Raffaele Marino
L. Buffoni
Lorenzo Chicchi
Lorenzo Giambagli
Duccio Fanelli
98
1
0
22 Dec 2023
Complex Recurrent Spectral Network
Complex Recurrent Spectral Network
Lorenzo Chicchi
Lorenzo Giambagli
L. Buffoni
Raffaele Marino
Duccio Fanelli
67
6
0
12 Dec 2023
Stochastic Gradient Descent-like relaxation is equivalent to Metropolis
  dynamics in discrete optimization and inference problems
Stochastic Gradient Descent-like relaxation is equivalent to Metropolis dynamics in discrete optimization and inference problems
Maria Chiara Angelini
A. Cavaliere
Raffaele Marino
F. Ricci-Tersenghi
124
5
0
11 Sep 2023
Eight challenges in developing theory of intelligence
Eight challenges in developing theory of intelligence
Haiping Huang
98
7
0
20 Jun 2023
Phase transitions in the mini-batch size for sparse and dense two-layer
  neural networks
Phase transitions in the mini-batch size for sparse and dense two-layer neural networks
Raffaele Marino
F. Ricci-Tersenghi
110
15
0
10 May 2023
Typical and atypical solutions in non-convex neural networks with
  discrete and continuous weights
Typical and atypical solutions in non-convex neural networks with discrete and continuous weights
Carlo Baldassi
Enrico M. Malatesta
Gabriele Perugini
R. Zecchina
MQ
92
13
0
26 Apr 2023
Storage and Learning phase transitions in the Random-Features Hopfield
  Model
Storage and Learning phase transitions in the Random-Features Hopfield Model
M. Negri
Clarissa Lauditi
Gabriele Perugini
Carlo Lucibello
Enrico M. Malatesta
28
16
0
29 Mar 2023
Inversion dynamics of class manifolds in deep learning reveals tradeoffs
  underlying generalisation
Inversion dynamics of class manifolds in deep learning reveals tradeoffs underlying generalisation
Simone Ciceri
Lorenzo Cassani
Matteo Osella
P. Rotondo
P. Pizzochero
M. Gherardi
76
7
0
09 Mar 2023
Deep Networks on Toroids: Removing Symmetries Reveals the Structure of
  Flat Regions in the Landscape Geometry
Deep Networks on Toroids: Removing Symmetries Reveals the Structure of Flat Regions in the Landscape Geometry
Fabrizio Pittorino
Antonio Ferraro
Gabriele Perugini
Christoph Feinauer
Carlo Baldassi
R. Zecchina
265
26
0
07 Feb 2022
Quantum Approximate Optimization Algorithm applied to the binary
  perceptron
Quantum Approximate Optimization Algorithm applied to the binary perceptron
Pietro Torta
G. Mbeng
Carlo Baldassi
R. Zecchina
G. Santoro
44
8
0
19 Dec 2021
Equivalence between algorithmic instability and transition to replica
  symmetry breaking in perceptron learning systems
Equivalence between algorithmic instability and transition to replica symmetry breaking in perceptron learning systems
Yang Zhao
Junbin Qiu
Mingshan Xie
Haiping Huang
27
4
0
26 Nov 2021
1