Cover Image

Memorization and Generalization in Generative Diffusion under the Manifold Hypothesis

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Achilli, Beatrice, Ambrogioni, Luca, Lucibello, Carlo, Mézard, Marc, Ventura, Enrico
Format:	Preprint
Published:	2025
Subjects:	Disordered Systems and Neural Networks
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Capacity of Modern Hopfield Networks under the Data Manifold Hypothesis
by: Achilli, Beatrice, et al.
Published: (2025)

Emergence of Distortions in High-Dimensional Guided Diffusion Models
by: Ventura, Enrico, et al.
Published: (2026)

Theory of Speciation Transitions in Diffusion Models with General Class Structure
by: Achilli, Beatrice, et al.
Published: (2026)

The Exponential Capacity of Dense Associative Memories
by: Lucibello, Carlo, et al.
Published: (2023)

Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training
by: Bonnaire, Tony, et al.
Published: (2025)

Biased Generalization in Diffusion Models
by: Garnier-Brun, Jerome, et al.
Published: (2026)

Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms
by: Demyanenko, Elizaveta, et al.
Published: (2025)

Memorization to Generalization: Emergence of Diffusion Models from Associative Memory
by: Pham, Bao, et al.
Published: (2025)

The phase diagram of compressed sensing with $\ell_0$-norm regularization
by: Barbier, Damien, et al.
Published: (2024)

Overlap Gap and Computational Thresholds in the Square Wave Perceptron
by: Benedetti, Marco, et al.
Published: (2025)

Kernel Density Estimators in Large Dimensions
by: Biroli, Giulio, et al.
Published: (2024)

Random Features Hopfield Networks generalize retrieval to previously unseen examples
by: Kalaj, Silvio, et al.
Published: (2024)

Demolition and Reinforcement of Memories in Spin-Glass-like Neural Networks
by: Ventura, Enrico
Published: (2024)

Learning and Unlearning: Bridging classification, memory and generative modeling in Recurrent Neural Networks
by: Ventura, Enrico
Published: (2024)

The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
by: Nicoletti, Flavio, et al.
Published: (2026)

Dynamical Learning in Deep Asymmetric Recurrent Neural Networks
by: Badalotti, Davide, et al.
Published: (2025)

Escape dynamics and implicit bias of one-pass SGD in overparameterized quadratic networks
by: Bocchi, Dario, et al.
Published: (2026)

Unlearning regularization for Boltzmann Machines
by: Ventura, Enrico, et al.
Published: (2023)

Training neural networks with structured noise improves classification and generalization
by: Benedetti, Marco, et al.
Published: (2023)

The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks
by: Farné, Gabriele, et al.
Published: (2026)

How transformers learn structured data: insights from hierarchical filtering
by: Garnier-Brun, Jerome, et al.
Published: (2024)

Are Neural Networks Collision Resistant?
by: Benedetti, Marco, et al.
Published: (2025)

Renormalization Group flow, Optimal Transport and Diffusion-based Generative Model
by: Sheshmani, Artan, et al.
Published: (2024)

Benchmarking Graph Neural Networks in Solving Hard Constraint Satisfaction Problems
by: Skenderi, Geri, et al.
Published: (2026)

Properties of the geometry of solutions and capacity of multi-layer neural networks with Rectified Linear Units activations
by: Baldassi, Carlo, et al.
Published: (2019)

Generalized hetero-associative neural networks
by: Agliari, Elena, et al.
Published: (2024)

Computer Generation of Disordered Networks with Targeted Structural Properties
by: Hemmann, Florin, et al.
Published: (2026)

Quantum engineering for compactly localized states in disordered Lieb lattices
by: Danieli, Carlo, et al.
Published: (2023)

A Generative Diffusion Model for Amorphous Materials
by: Yang, Kai, et al.
Published: (2025)

Generative random latent features models and statistics of natural images
by: Fleig, Philipp, et al.
Published: (2022)

DisQu: Investigating the Impact of Disorder in Quantum Generative Models
by: Werner, Yannick, et al.
Published: (2024)

Isolating the hard core of phaseless inference: the Phase selection formulation
by: Straziota, Davide, et al.
Published: (2025)

The scaling behaviour of localised and extended states in one-dimensional tight-binding models with disorder
by: Schaefer, Luca, et al.
Published: (2024)

The different localisation properties of the eigenmodes of the Laplacian and adjacency matrix of 2D random geometric graphs
by: Schaefer, Luca, et al.
Published: (2026)

Generalized Aubry-André-Harper model with power-law quasiperiodic potentials
by: Wang, Ya-Nan, et al.
Published: (2025)

Nonequilibrium DC Current Generation in a Driven Dissipative Haldane Model
by: Koenigsmann, Konrad, et al.
Published: (2025)

Generalizations of Parisi's replica symmetry breaking and overlaps in random energy models
by: Derrida, Bernard, et al.
Published: (2024)

Soft Quantization: Model Compression Via Weight Coupling
by: Bernstein, Daniel T., et al.
Published: (2026)

Auxiliary Physics-Informed Neural Networks for Forward, Inverse, and Coupled Radiative Transfer Problems
by: Riganti, Roberto, et al.
Published: (2023)

Generic non-Hermitian mobility edges in a class of duality-breaking quasicrystals
by: Jiang, Xiang-Ping, et al.
Published: (2024)