Cover Image

What's Inside Your Diffusion Model? A Score-Based Riemannian Metric to Explore the Data Manifold

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Azeglio, Simone, Di Bernardo, Arianna
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

What Secrets Do Your Manifolds Hold? Understanding the Local Geometry of Generative Models
by: Humayun, Ahmed Imtiaz, et al.
Published: (2024)

Exploring Time Conditioning in Diffusion Generative Models from Disjoint Noisy Data Manifolds
by: Li, Liuzhuozheng, et al.
Published: (2026)

Convolution goes higher-order: a biologically inspired mechanism empowers image classification
by: Azeglio, Simone, et al.
Published: (2024)

Be Tangential to Manifold: Discovering Riemannian Metric for Diffusion Models
by: Saito, Shinnosuke, et al.
Published: (2025)

ManifoldGD: Training-Free Hierarchical Manifold Guidance for Diffusion-Based Dataset Distillation
by: Roy, Ayush, et al.
Published: (2026)

Image Interpolation with Score-based Riemannian Metrics of Diffusion Models
by: Saito, Shinnosuke, et al.
Published: (2025)

Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models
by: Chen, Tianqi, et al.
Published: (2024)

Exploring Structured Semantic Priors Underlying Diffusion Score for Test-time Adaptation
by: Li, Mingjia, et al.
Published: (2025)

Higher-Order Convolution Improves Neural Predictivity in the Retina
by: Azeglio, Simone, et al.
Published: (2025)

Flows and Diffusions on the Neural Manifold
by: Saragih, Daniel, et al.
Published: (2025)

Score-based Membership Inference on Diffusion Models
by: Rao, Mingxing, et al.
Published: (2025)

3D CBCT Artefact Removal Using Perpendicular Score-Based Diffusion Models
by: Schaub, Susanne, et al.
Published: (2026)

Nearest Neighbour Score Estimators for Diffusion Generative Models
by: Niedoba, Matthew, et al.
Published: (2024)

Your Diffusion Model is Secretly a Certifiably Robust Classifier
by: Chen, Huanran, et al.
Published: (2024)

Align Your Steps: Optimizing Sampling Schedules in Diffusion Models
by: Sabour, Amirmojtaba, et al.
Published: (2024)

ScoreMix: Synthetic Data Generation by Score Composition in Diffusion Models Improves Recognition
by: Rahimi, Parsa, et al.
Published: (2025)

What is Adversarial Training for Diffusion Models?
by: Rosaria, Briglia Maria, et al.
Published: (2025)

Metric Unreliability in Multimodal Machine Unlearning: A Systematic Analysis and Principled Unified Score
by: Khan, Abdullah Ahmad, et al.
Published: (2026)

How I Met Your Bias: Investigating Bias Amplification in Diffusion Models
by: Roos, Nathan, et al.
Published: (2025)

Follow Your Heart: Landmark-Guided Transducer Pose Scoring for Point-of-Care Echocardiography
by: Guo, Zaiyang, et al.
Published: (2026)

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders
by: Kumar, Amandeep, et al.
Published: (2026)

Derivative-Free Diffusion Manifold-Constrained Gradient for Unified XAI
by: Kim, Won Jun, et al.
Published: (2024)

Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models
by: Bellchambers, Gregory
Published: (2025)

DiFiC: Your Diffusion Model Holds the Secret to Fine-Grained Clustering
by: Yang, Ruohong, et al.
Published: (2024)

Align Your Tangent: Training Better Consistency Models via Manifold-Aligned Tangents
by: Kim, Beomsu, et al.
Published: (2025)

The Manifold Hypothesis for Gradient-Based Explanations
by: Bordt, Sebastian, et al.
Published: (2022)

Affordance Labeling and Exploration: A Manifold-Based Approach
by: Özçil, İsmail, et al.
Published: (2024)

Preserve Your Own Correlation: A Noise Prior for Video Diffusion Models
by: Ge, Songwei, et al.
Published: (2023)

Varying Manifolds in Diffusion: From Time-varying Geometries to Visual Saliency
by: Chen, Junhao, et al.
Published: (2024)

How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
by: Chang, Pascal, et al.
Published: (2025)

What's on Your Plate? Inferring Chinese Cuisine Intake from Wearable IMUs
by: Yin, Jiaxi, et al.
Published: (2025)

EHRDiff: Exploring Realistic EHR Synthesis with Diffusion Models
by: Yuan, Hongyi, et al.
Published: (2023)

Few-Step Diffusion via Score identity Distillation
by: Zhou, Mingyuan, et al.
Published: (2025)

Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection
by: Yang, Yang, et al.
Published: (2022)

Harnessing Data Asymmetry: Manifold Learning in the Finsler World
by: Dagès, Thomas, et al.
Published: (2026)

Shape-Guided Diffusion with Inside-Outside Attention
by: Park, Dong Huk, et al.
Published: (2022)

Score-Based Multimodal Autoencoder
by: Wesego, Daniel, et al.
Published: (2023)

Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Models
by: Ling, Huan, et al.
Published: (2023)

Lay-Your-Scene: Natural Scene Layout Generation with Diffusion Transformers
by: Srivastava, Divyansh, et al.
Published: (2025)

CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
by: Chung, Hyungjin, et al.
Published: (2024)