:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Hamad, Hussen Abu, Rosenbaum, Dan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2512.23853
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robust Neural Processes for Noisy Data
by: Shapira, Chen, et al.
Published: (2024)

EventFlow: Forecasting Temporal Point Processes with Flow Matching
by: Kerrigan, Gavin, et al.
Published: (2024)

Edit-Based Flow Matching for Temporal Point Processes
by: Lüdke, David, et al.
Published: (2025)

Stochastic Process Learning via Operator Flow Matching
by: Shi, Yaozhong, et al.
Published: (2025)

ContinualFlow: Learning and Unlearning with Neural Flow Matching
by: Simone, Lorenzo, et al.
Published: (2025)

Flow to Learn: Flow Matching on Neural Network Parameters
by: Saragih, Daniel, et al.
Published: (2025)

FNODE: Flow-Matching for data-driven simulation of constrained multibody systems
by: Wang, Hongyu, et al.
Published: (2025)

On the relationship between predictive coding and backpropagation
by: Rosenbaum, Robert
Published: (2021)

Flow Matching: Markov Kernels, Stochastic Processes and Transport Plans
by: Wald, Christian, et al.
Published: (2025)

DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights
by: Gupta, Saumya, et al.
Published: (2026)

Explicit Flow Matching: On The Theory of Flow Matching Algorithms with Applications
by: Ryzhakov, Gleb, et al.
Published: (2024)

Gradient Flow Matching for Learning Update Dynamics in Neural Network Training
by: Shou, Xiao, et al.
Published: (2025)

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

Random Process Flow Matching: Generative Implicit Representations of Multivariate Random Fields
by: Lalanne, Julien, et al.
Published: (2026)

Generative Latent Neural PDE Solver using Flow Matching
by: Li, Zijie, et al.
Published: (2025)

Coupled Flow Matching
by: Cai, Wenxi, et al.
Published: (2025)

Federated Flow Matching
by: Wang, Zifan, et al.
Published: (2025)

On the Guidance of Flow Matching
by: Feng, Ruiqi, et al.
Published: (2025)

Probabilistic Prediction of Neural Dynamics via Autoregressive Flow Matching
by: Rogalla, Nicole, et al.
Published: (2026)

Reflected Flow Matching
by: Xie, Tianyu, et al.
Published: (2024)

Active Flow Matching
by: Grewal, Yashvir S., et al.
Published: (2026)

Flow Matching with Gaussian Process Priors for Probabilistic Time Series Forecasting
by: Kollovieh, Marcel, et al.
Published: (2024)

VeriFlow: Modeling Distributions for Neural Network Verification
by: Zaid, Faried Abu, et al.
Published: (2024)

Formally Verifying Analog Neural Networks Under Process Variations Using Polynomial Zonotopes
by: Abu-Haeyeh, Yasmine, et al.
Published: (2026)

From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
by: Li, Xin, et al.
Published: (2024)

Euphonium: Steering Video Flow Matching via Process Reward Gradient Guided Stochastic Dynamics
by: Zhong, Ruizhe, et al.
Published: (2026)

Source-Guided Flow Matching
by: Wang, Zifan, et al.
Published: (2025)

Flow Matching with Semidiscrete Couplings
by: Mousavi-Hosseini, Alireza, et al.
Published: (2025)

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

Risk-Entropic Flow Matching
by: Ramezani, Vahid R., et al.
Published: (2025)

Structured Coupling for Flow Matching
by: Sumba, Xavier, et al.
Published: (2026)

Low-Pass Flow Matching
by: Ruscio, Francesco M., et al.
Published: (2026)

Preference Alignment with Flow Matching
by: Kim, Minu, et al.
Published: (2024)

Flow Matching Guide and Code
by: Lipman, Yaron, et al.
Published: (2024)

Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching
by: Wan, Zhengyan, et al.
Published: (2025)

Isokinetic Flow Matching for Pathwise Straightening of Generative Flows
by: Khan, Tauhid
Published: (2026)

Neural Bipartite Matching
by: Georgiev, Dobrik, et al.
Published: (2020)

Drift Flow Matching
by: Ma, Chenrui, et al.
Published: (2026)

Discrete Flow Matching
by: Gat, Itai, et al.
Published: (2024)

Physics-Informed Design of Input Convex Neural Networks for Consistency Optimal Transport Flow Matching
by: Song, Fanghui, et al.
Published: (2025)