Dynamical Regimes of Multimodal Diffusion Models
Fuente:
arXiv
Saved in:
| Main Authors: | Albrychiewicz, Emil, Valiente, Andrés Franco, Chen, Li-Ching |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Interpreting the Synchronization Gap: The Hidden Mechanism Inside Diffusion Transformers
by: Albrychiewicz, Emil, et al.
Published: (2026)
by: Albrychiewicz, Emil, et al.
Published: (2026)
The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
by: Nicoletti, Flavio, et al.
Published: (2026)
by: Nicoletti, Flavio, et al.
Published: (2026)
Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training
by: Bonnaire, Tony, et al.
Published: (2025)
by: Bonnaire, Tony, et al.
Published: (2025)
Kernel Renormalization in Bayesian Deep Neural Networks: the Equivalent Wishart Ansatz in the Proportional Regime
by: Baglioni, Paolo, et al.
Published: (2026)
by: Baglioni, Paolo, et al.
Published: (2026)
A Generative Diffusion Model for Amorphous Materials
by: Yang, Kai, et al.
Published: (2025)
by: Yang, Kai, et al.
Published: (2025)
Emergence of Distortions in High-Dimensional Guided Diffusion Models
by: Ventura, Enrico, et al.
Published: (2026)
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)
by: Achilli, Beatrice, et al.
Published: (2026)
Probing the Latent Hierarchical Structure of Data via Diffusion Models
by: Sclocchi, Antonio, et al.
Published: (2024)
by: Sclocchi, Antonio, et al.
Published: (2024)
A Dynamical Model of Neural Scaling Laws
by: Bordelon, Blake, et al.
Published: (2024)
by: Bordelon, Blake, et al.
Published: (2024)
Generalization Dynamics of Linear Diffusion Models
by: Merger, Claudia, et al.
Published: (2025)
by: Merger, Claudia, et al.
Published: (2025)
Training Dynamics of Nonlinear Contrastive Learning Model in the High Dimensional Limit
by: Meng, Lineghuan, et al.
Published: (2024)
by: Meng, Lineghuan, et al.
Published: (2024)
Two-Point Deterministic Equivalence for Stochastic Gradient Dynamics in Linear Models
by: Atanasov, Alexander, et al.
Published: (2025)
by: Atanasov, Alexander, et al.
Published: (2025)
Dynamics of Meta-learning Representation in the Teacher-student Scenario
by: Wang, Hui, et al.
Published: (2024)
by: Wang, Hui, et al.
Published: (2024)
Diffusion Operator Geometry of Feedforward Representations
by: Reddy, Kanishka
Published: (2026)
by: Reddy, Kanishka
Published: (2026)
Sampling Data with Chains of Forward-Backward Diffusion Steps
by: Kang, Hyunmo, et al.
Published: (2026)
by: Kang, Hyunmo, et al.
Published: (2026)
Precise Dynamics of Diagonal Linear Networks: A Unifying Analysis by Dynamical Mean-Field Theory
by: Nishiyama, Sota, et al.
Published: (2025)
by: Nishiyama, Sota, et al.
Published: (2025)
Infinite Limits of Multi-head Transformer Dynamics
by: Bordelon, Blake, et al.
Published: (2024)
by: Bordelon, Blake, et al.
Published: (2024)
Geometric Dynamics of Signal Propagation Predict Trainability of Transformers
by: Cowsik, Aditya, et al.
Published: (2024)
by: Cowsik, Aditya, et al.
Published: (2024)
Grokking as the Transition from Lazy to Rich Training Dynamics
by: Kumar, Tanishq, et al.
Published: (2023)
by: Kumar, Tanishq, et al.
Published: (2023)
The RL Perceptron: Generalisation Dynamics of Policy Learning in High Dimensions
by: Patel, Nishil, et al.
Published: (2023)
by: Patel, Nishil, et al.
Published: (2023)
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training
by: Jain, Anchit, et al.
Published: (2024)
by: Jain, Anchit, et al.
Published: (2024)
Growing Neural Networks: Dynamic Evolution through Gradient Descent
by: Radhakrishnan, Anil, et al.
Published: (2025)
by: Radhakrishnan, Anil, et al.
Published: (2025)
Dynamical Decoupling of Generalization and Overfitting in Large Two-Layer Networks
by: Montanari, Andrea, et al.
Published: (2025)
by: Montanari, Andrea, et al.
Published: (2025)
Dynamical Mean-Field Theory of Self-Attention Neural Networks
by: Poc-López, Ángel, et al.
Published: (2024)
by: Poc-López, Ángel, et al.
Published: (2024)
Disordered Dynamics in High Dimensions: Connections to Random Matrices and Machine Learning
by: Bordelon, Blake, et al.
Published: (2026)
by: Bordelon, Blake, et al.
Published: (2026)
Controlled Langevin Dynamics for Sampling of Feedforward Neural Networks Trained with Minibatches
by: Zambon, Alessandro, et al.
Published: (2026)
by: Zambon, Alessandro, et al.
Published: (2026)
High-Dimensional Limit of Stochastic Gradient Flow via Dynamical Mean-Field Theory
by: Nishiyama, Sota, et al.
Published: (2026)
by: Nishiyama, Sota, et al.
Published: (2026)
Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features
by: Veiga, Rodrigo, et al.
Published: (2024)
by: Veiga, Rodrigo, et al.
Published: (2024)
Exact Learning Dynamics of In-Context Learning in Linear Transformers and Its Application to Non-Linear Transformers
by: Mainali, Nischal, et al.
Published: (2025)
by: Mainali, Nischal, et al.
Published: (2025)
Siamese Neural Network for Label-Efficient Critical Phenomena Prediction in 3D Percolation Models
by: Wang, Shanshan, et al.
Published: (2025)
by: Wang, Shanshan, et al.
Published: (2025)
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
by: Bordelon, Blake, et al.
Published: (2025)
by: Bordelon, Blake, et al.
Published: (2025)
The Quantization Model of Neural Scaling
by: Michaud, Eric J., et al.
Published: (2023)
by: Michaud, Eric J., et al.
Published: (2023)
Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime
by: Defilippis, Leonardo, et al.
Published: (2025)
by: Defilippis, Leonardo, et al.
Published: (2025)
Critical Phase Transition in Large Language Models
by: Nakaishi, Kai, et al.
Published: (2024)
by: Nakaishi, Kai, et al.
Published: (2024)
Biased Generalization in Diffusion Models
by: Garnier-Brun, Jerome, et al.
Published: (2026)
by: Garnier-Brun, Jerome, et al.
Published: (2026)
Soft Quantization: Model Compression Via Weight Coupling
by: Bernstein, Daniel T., et al.
Published: (2026)
by: Bernstein, Daniel T., et al.
Published: (2026)
The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks
by: Farné, Gabriele, et al.
Published: (2026)
by: Farné, Gabriele, et al.
Published: (2026)
Optimal Spectral Transitions in High-Dimensional Multi-Index Models
by: Defilippis, Leonardo, et al.
Published: (2025)
by: Defilippis, Leonardo, et al.
Published: (2025)
The Effect of Optimal Self-Distillation in Noisy Gaussian Mixture Model
by: Takanami, Kaito, et al.
Published: (2025)
by: Takanami, Kaito, et al.
Published: (2025)
EB-RANSAC: Random Sample Consensus based on Energy-Based Model
by: Yasuda, Muneki, et al.
Published: (2026)
by: Yasuda, Muneki, et al.
Published: (2026)
Similar Items
-
Interpreting the Synchronization Gap: The Hidden Mechanism Inside Diffusion Transformers
by: Albrychiewicz, Emil, et al.
Published: (2026) -
The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models
by: Nicoletti, Flavio, et al.
Published: (2026) -
Why Diffusion Models Don't Memorize: The Role of Implicit Dynamical Regularization in Training
by: Bonnaire, Tony, et al.
Published: (2025) -
Kernel Renormalization in Bayesian Deep Neural Networks: the Equivalent Wishart Ansatz in the Proportional Regime
by: Baglioni, Paolo, et al.
Published: (2026) -
A Generative Diffusion Model for Amorphous Materials
by: Yang, Kai, et al.
Published: (2025)