Cover Image

Elucidating Flow Matching ODE Dynamics with Respect to Data Geometries and Denoisers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wan, Zhengchao, Wang, Qingsong, Mishne, Gal, Wang, Yusu
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

The Numerical Stability of Hyperbolic Representation Learning
by: Mishne, Gal, et al.
Published: (2022)

Comparing Graph Transformers via Positional Encodings
by: Black, Mitchell, et al.
Published: (2024)

Two Calm Ends and the Wild Middle: A Geometric Picture of Memorization in Diffusion Models
by: Dodson, Nick, et al.
Published: (2026)

Explaining GNN Explanations with Edge Gradients
by: He, Jesse, et al.
Published: (2025)

Distances for Markov Chains, and Their Differentiation
by: Brugère, Tristan, et al.
Published: (2023)

FlowCast-ODE: Continuous Hourly Weather Forecasting with Dynamic Flow Matching and ODE Solver
by: He, Shuangshuang, et al.
Published: (2025)

Learning Cartesian Product Graphs with Laplacian Constraints
by: Shi, Changhao, et al.
Published: (2024)

MINAR: Mechanistic Interpretability for Neural Algorithmic Reasoning
by: He, Jesse, et al.
Published: (2026)

Robust Graph-Based Semi-Supervised Learning via $p$-Conductances
by: Robertson, Sawyer Jack, et al.
Published: (2025)

Graph Laplacian Learning with Exponential Family Noise
by: Shi, Changhao, et al.
Published: (2023)

Learning Kronecker-Structured Graphs from Smooth Signals
by: Shi, Changhao, et al.
Published: (2025)

General and Efficient Steering of Unconditional Diffusion
by: Wang, Qingsong, et al.
Published: (2026)

Deep and shallow data science for multi-scale optical neuroscience
by: Mishne, Gal, et al.
Published: (2024)

SiBBlInGS: Similarity-driven Building-Block Inference using Graphs across States
by: Mudrik, Noga, et al.
Published: (2023)

Revisiting Meta-Learning with Noisy Labels: Reweighting Dynamics and Theoretical Guarantees
by: Zhang, Yiming, et al.
Published: (2025)

Cluster and then Embed: A Modular Approach for Visualization
by: Coda, Elizabeth, et al.
Published: (2025)

Elucidating the Design Choice of Probability Paths in Flow Matching for Forecasting
by: Lim, Soon Hoe, et al.
Published: (2024)

Tree-Wasserstein Distance for High Dimensional Data with a Latent Feature Hierarchy
by: Lin, Ya-Wei Eileen, et al.
Published: (2024)

Multiway Multislice PHATE: Visualizing Hidden Dynamics of RNNs through Training
by: Xie, Jiancheng, et al.
Published: (2024)

ODE-free Neural Flow Matching for One-Step Generative Modeling
by: Shou, Xiao
Published: (2026)

Stiefel Flow Matching for Moment-Constrained Structure Elucidation
by: Cheng, Austin, et al.
Published: (2024)

From Euler to Dormand-Prince: ODE Solvers for Flow Matching Generative Models
by: Xiao, Hao
Published: (2026)

Unsupervised Feature Selection Through Group Discovery
by: Lifshitz, Shira, et al.
Published: (2025)

FlowMS: Flow Matching for De Novo Structure Elucidation from Mass Spectra
by: Nie, Jianan, et al.
Published: (2026)

Robust Tangent Space Estimation via Laplacian Eigenvector Gradient Orthogonalization
by: Kohli, Dhruv, et al.
Published: (2025)

Multi-Integration of Labels across Categories for Component Identification (MILCCI)
by: Mudrik, Noga, et al.
Published: (2026)

Pioneer: Physics-informed Riemannian Graph ODE for Entropy-increasing Dynamics
by: Sun, Li, et al.
Published: (2025)

Composite Flow Matching for Reinforcement Learning with Shifted-Dynamics Data
by: Kong, Lingkai, et al.
Published: (2025)

Advanced Global Wildfire Activity Modeling with Hierarchical Graph ODE
by: Xu, Fan, et al.
Published: (2026)

Joint Hierarchical Representation Learning of Samples and Features via Informed Tree-Wasserstein Distance
by: Lin, Ya-Wei Eileen, et al.
Published: (2025)

Semi-Supervised Laplace Learning on Stiefel Manifolds
by: Holtz, Chester, et al.
Published: (2023)

Flow Matching on General Geometries
by: Chen, Ricky T. Q., et al.
Published: (2023)

Coupled Transformer Autoencoder for Disentangling Multi-Region Neural Latent Dynamics
by: Sristi, Ram Dyuthi, et al.
Published: (2025)

Weighted Conditional Flow Matching
by: Calvo-Ordonez, Sergio, et al.
Published: (2025)

Dynamics-Level Watermarking of Flow Matching Models with Random Codes
by: Wang, Shuchan
Published: (2026)

Learning Ultrametric Trees for Optimal Transport Regression
by: Chen, Samantha, et al.
Published: (2022)

What Time Is It? How Data Geometry Makes Time Conditioning Optional for Flow Matching
by: Helbling, Alec, et al.
Published: (2026)

The Wasserstein transform
by: Jin, Kun, et al.
Published: (2018)

Understanding Dynamics of Adam in Zero-Sum Games: An ODE Approach
by: Feng, Yi, et al.
Published: (2026)

DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models
by: Wen, Haomin, et al.
Published: (2023)