Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian probability distributions
Fuente:
arXiv
Saved in:
| Main Authors: | Cole, Frank, Lu, Yulong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Theory of Diversity for Random Matrices with Applications to In-Context Learning of Schrödinger Equations
by: Cole, Frank, et al.
Published: (2026)
by: Cole, Frank, et al.
Published: (2026)
In-Context Learning of Linear Dynamical Systems with Transformers: Approximation Bounds and Depth-Separation
by: Cole, Frank, et al.
Published: (2025)
by: Cole, Frank, et al.
Published: (2025)
Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions
by: Tran, Hoang, et al.
Published: (2025)
by: Tran, Hoang, et al.
Published: (2025)
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator Learning
by: Cole, Frank, et al.
Published: (2024)
by: Cole, Frank, et al.
Published: (2024)
Breaking the curse of dimensionality for linear rules: optimal predictors over the ellipsoid
by: Ayme, Alexis, et al.
Published: (2025)
by: Ayme, Alexis, et al.
Published: (2025)
Does the Barron space really defy the curse of dimensionality?
by: Schavemaker, Olov
Published: (2025)
by: Schavemaker, Olov
Published: (2025)
Squared families: Searching beyond regular probability models
by: Tsuchida, Russell, et al.
Published: (2025)
by: Tsuchida, Russell, et al.
Published: (2025)
Flow-based generative models as iterative algorithms in probability space
by: Xie, Yao, et al.
Published: (2025)
by: Xie, Yao, et al.
Published: (2025)
Equivariant score-based generative models provably learn distributions with symmetries efficiently
by: Chen, Ziyu, et al.
Published: (2024)
by: Chen, Ziyu, et al.
Published: (2024)
Generalizing Score-based generative models for Heavy-tailed Distributions
by: Fassina, Tiziano, et al.
Published: (2026)
by: Fassina, Tiziano, et al.
Published: (2026)
The curse of random quantum data
by: Zhang, Kaining, et al.
Published: (2024)
by: Zhang, Kaining, et al.
Published: (2024)
Deep generative models as the probability transformation functions
by: Bondar, Vitalii, et al.
Published: (2025)
by: Bondar, Vitalii, et al.
Published: (2025)
Game-theoretic distributed learning of generative models for heterogeneous data collections
by: Schlesinger, Dmitrij, et al.
Published: (2025)
by: Schlesinger, Dmitrij, et al.
Published: (2025)
Nonparametric estimation of conditional probability distributions using a generative approach based on conditional push-forward neural networks
by: Franco, Nicola Rares, et al.
Published: (2025)
by: Franco, Nicola Rares, et al.
Published: (2025)
Bilinear representation mitigates reversal curse and enables consistent model editing
by: Kim, Dong-Kyum, et al.
Published: (2025)
by: Kim, Dong-Kyum, et al.
Published: (2025)
InFusionLayer: a CFA-based ensemble tool to generate new classifiers for learning and modeling
by: Roginek, Eric, et al.
Published: (2026)
by: Roginek, Eric, et al.
Published: (2026)
Score-based generative models are provably robust: an uncertainty quantification perspective
by: Mimikos-Stamatopoulos, Nikiforos, et al.
Published: (2024)
by: Mimikos-Stamatopoulos, Nikiforos, et al.
Published: (2024)
The statistical thermodynamics of generative diffusion models: Phase transitions, symmetry breaking and critical instability
by: Ambrogioni, Luca
Published: (2023)
by: Ambrogioni, Luca
Published: (2023)
Diffusion models learn distributions generated by complex Langevin dynamics
by: Habibi, Diaa E., et al.
Published: (2024)
by: Habibi, Diaa E., et al.
Published: (2024)
Analysis of learning a flow-based generative model from limited sample complexity
by: Cui, Hugo, et al.
Published: (2023)
by: Cui, Hugo, et al.
Published: (2023)
Spherical Boltzmann machines: a solvable theory of learning and generation in energy-based models
by: Tulinski, Thomas, et al.
Published: (2026)
by: Tulinski, Thomas, et al.
Published: (2026)
Mixed Membership sub-Gaussian Models
by: Qing, Huan
Published: (2026)
by: Qing, Huan
Published: (2026)
Score-based 3D molecule generation with neural fields
by: Kirchmeyer, Matthieu, et al.
Published: (2025)
by: Kirchmeyer, Matthieu, et al.
Published: (2025)
Individual-heterogeneous sub-Gaussian Mixture Models
by: Qing, Huan
Published: (2026)
by: Qing, Huan
Published: (2026)
Score-based generative emulation of impact-relevant Earth system model outputs
by: Bouabid, Shahine, et al.
Published: (2025)
by: Bouabid, Shahine, et al.
Published: (2025)
Wasserstein Flow Matching: Generative modeling over families of distributions
by: Haviv, Doron, et al.
Published: (2024)
by: Haviv, Doron, et al.
Published: (2024)
Photon detection probability prediction using one-dimensional generative neural network
by: Mu, Wei, et al.
Published: (2021)
by: Mu, Wei, et al.
Published: (2021)
On Forgetting and Stability of Score-based Generative models
by: Strasman, Stanislas, et al.
Published: (2026)
by: Strasman, Stanislas, et al.
Published: (2026)
Structure learning with Temporal Gaussian Mixture for model-based Reinforcement Learning
by: Champion, Théophile, et al.
Published: (2024)
by: Champion, Théophile, et al.
Published: (2024)
Uniting contrastive and generative learning for event sequences models
by: Yugay, Aleksandr, et al.
Published: (2024)
by: Yugay, Aleksandr, et al.
Published: (2024)
A solvable model of learning generative diffusion: theory and insights
by: Cui, Hugo, et al.
Published: (2025)
by: Cui, Hugo, et al.
Published: (2025)
Schrödinger bridge based deep conditional generative learning
by: Huang, Hanwen
Published: (2024)
by: Huang, Hanwen
Published: (2024)
The distribution of calibrated likelihood functions on the probability-likelihood Aitchison simplex
by: Noé, Paul-Gauthier, et al.
Published: (2025)
by: Noé, Paul-Gauthier, et al.
Published: (2025)
Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
by: Karwowski, Jacek, et al.
Published: (2025)
by: Karwowski, Jacek, et al.
Published: (2025)
Identifying counterfactual probabilities using bivariate distributions and uplift modeling
by: Verhelst, Théo, et al.
Published: (2025)
by: Verhelst, Théo, et al.
Published: (2025)
In-Context Operator Learning on the Space of Probability Measures
by: Cole, Frank, et al.
Published: (2026)
by: Cole, Frank, et al.
Published: (2026)
Failure to Mix: Large language models struggle to answer according to desired probability distributions
by: Yang, Ivy Yuqian, et al.
Published: (2025)
by: Yang, Ivy Yuqian, et al.
Published: (2025)
Generative modeling of conditional probability distributions on the level-sets of collective variables
by: Akhyar, Fatima-Zahrae, et al.
Published: (2025)
by: Akhyar, Fatima-Zahrae, et al.
Published: (2025)
Quantum latent distributions in deep generative models
by: Bacarreza, Omar, et al.
Published: (2025)
by: Bacarreza, Omar, et al.
Published: (2025)
PoET: A generative model of protein families as sequences-of-sequences
by: Truong Jr, Timothy F., et al.
Published: (2023)
by: Truong Jr, Timothy F., et al.
Published: (2023)
Similar Items
-
A Theory of Diversity for Random Matrices with Applications to In-Context Learning of Schrödinger Equations
by: Cole, Frank, et al.
Published: (2026) -
In-Context Learning of Linear Dynamical Systems with Transformers: Approximation Bounds and Depth-Separation
by: Cole, Frank, et al.
Published: (2025) -
Diffusion-based supervised learning of generative models for efficient sampling of multimodal distributions
by: Tran, Hoang, et al.
Published: (2025) -
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator Learning
by: Cole, Frank, et al.
Published: (2024) -
Breaking the curse of dimensionality for linear rules: optimal predictors over the ellipsoid
by: Ayme, Alexis, et al.
Published: (2025)