Picture for Pierfrancesco Urbani

Pierfrancesco Urbani

Generative modeling through internal high-dimensional chaotic activity

Add code
May 17, 2024
Viaarxiv icon

Stochastic Gradient Descent outperforms Gradient Descent in recovering a high-dimensional signal in a glassy energy landscape

Add code
Sep 09, 2023
Viaarxiv icon

The effective noise of Stochastic Gradient Descent

Add code
Dec 20, 2021
Figure 1 for The effective noise of Stochastic Gradient Descent
Figure 2 for The effective noise of Stochastic Gradient Descent
Figure 3 for The effective noise of Stochastic Gradient Descent
Figure 4 for The effective noise of Stochastic Gradient Descent
Viaarxiv icon

Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems

Add code
Mar 11, 2021
Figure 1 for Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems
Figure 2 for Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems
Figure 3 for Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems
Figure 4 for Just a Momentum: Analytical Study of Momentum-Based Acceleration Methods in Paradigmatic High-Dimensional Non-Convex Problems
Viaarxiv icon

Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem

Add code
Mar 08, 2021
Figure 1 for Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem
Figure 2 for Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem
Figure 3 for Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem
Figure 4 for Stochasticity helps to navigate rough landscapes: comparing gradient-descent-based algorithms in the phase retrieval problem
Viaarxiv icon

Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval

Add code
Jun 12, 2020
Figure 1 for Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
Figure 2 for Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
Figure 3 for Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
Figure 4 for Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
Viaarxiv icon

Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification

Add code
Jun 10, 2020
Figure 1 for Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
Figure 2 for Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
Figure 3 for Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
Figure 4 for Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
Viaarxiv icon

Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model

Add code
Feb 01, 2019
Figure 1 for Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model
Figure 2 for Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model
Figure 3 for Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model
Figure 4 for Passed & Spurious: analysing descent algorithms and local minima in spiked matrix-tensor model
Viaarxiv icon

Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference

Add code
Dec 21, 2018
Figure 1 for Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference
Figure 2 for Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference
Figure 3 for Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference
Figure 4 for Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference
Viaarxiv icon

Approximate Survey Propagation for Statistical Inference

Add code
Jul 03, 2018
Figure 1 for Approximate Survey Propagation for Statistical Inference
Figure 2 for Approximate Survey Propagation for Statistical Inference
Figure 3 for Approximate Survey Propagation for Statistical Inference
Figure 4 for Approximate Survey Propagation for Statistical Inference
Viaarxiv icon