Giulio Biroli
14 papers · 2018–2026 · 5 venues · across top CS/AI venues
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Achievements
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🗺️ Taxonomy Completionist (25) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🐣 Hot Topic Early Bird
🏆
Keyword Champion
(2)
🧭
Keyword Pioneer
🗃️
Keyword Collector
(65)
💎
Century Club · Bronze
🔥
Unstoppable · Bronze
❓
The Questioner
(2)
Top co-authors
Research topics
Machine Learning
(13)
Optimization & Theory · Machine Learning
(13)
Deep Learning
(8)
Architectures
(6)
Core Methods
(3)
Optimization & Theory · Deep Learning
(3)
Learning Types · Deep Learning
(2)
Artificial Intelligence
(1)
Computer Vision
(1)
Mathematics & Optimization
(1)
Bayesian & Probabilistic
(1)
Core AI · Artificial Intelligence
(1)
Core AI · Computer Vision
(1)
Learning Types · Machine Learning
(1)
Models
(1)
Keywords
gradient flow
(4)
neural network
(4)
double descent
(3)
feature learning
(2)
mean field theory
(2)
non-convex optimization
(2)
shallow neural network
(2)
interpolation threshold
(2)
loss landscape
(2)
statistical physics
(2)
singular value decomposition
(1)
generalization error
(1)
gradient descent
(1)
signal recovery
(1)
variable selection
(1)
label noise
(1)
restricted boltzmann machine
(1)
vision transformer
(1)
generative model
(1)
phase retrieval
(1)
Papers
High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks
JMLR 2026
A Differentiable Rank-Based Objective for Better Feature Learning
ICLR 2025
Cascade of phase transitions in the training of energy-based models
NeurIPS 2024
On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions
AISTATS 2024
Neural Network Pruning Denoises the Features and Makes Local Connectivity Emerge in Visual Tasks
ICML 2022
ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases
ICML 2021
On the interplay between data structure and loss function in classification problems
NeurIPS 2021
An analytic theory of shallow networks dynamics for hinge loss classification
NeurIPS 2020
Complex Dynamics in Simple Neural Networks: Understanding Gradient Flow in Phase Retrieval
NeurIPS 2020
Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime
ICML 2020
Triple descent and the two kinds of overfitting: where & why do they appear?
NeurIPS 2020
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
NeurIPS 2019
Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models
NeurIPS 2019
Comparing Dynamics: Deep Neural Networks versus Glassy Systems
ICML 2018