:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Su, Junwei, Wu, Shan
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2508.14352
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations
by: Su, Junwei, et al.
Published: (2025)

Temporal-Aware Evaluation and Learning for Temporal Graph Neural Networks
by: Su, Junwei, et al.
Published: (2024)

On the Topology Awareness and Generalization Performance of Graph Neural Networks
by: Su, Junwei, et al.
Published: (2024)

On the Interplay between Graph Structure and Learning Algorithms in Graph Neural Networks
by: Su, Junwei, et al.
Published: (2025)

MTRGL:Effective Temporal Correlation Discerning through Multi-modal Temporal Relational Graph Learning
by: Su, Junwei, et al.
Published: (2024)

DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation
by: Shing, Makoto, et al.
Published: (2025)

Generating Graphs via Spectral Diffusion
by: Minello, Giorgia, et al.
Published: (2024)

Hypergraph Generation via Structured Stochastic Diffusion
by: Nemeth, Christopher
Published: (2026)

Improving Implicit Regularization of SGD with Preconditioning for Least Square Problems
by: Su, Junwei, et al.
Published: (2024)

Improving Discrete Diffusion Models via Structured Preferential Generation
by: Rissanen, Severi, et al.
Published: (2024)

From Tokens to Blocks: A Block-Diffusion Perspective on Molecular Generation
by: Yang, Qianwei, et al.
Published: (2026)

Towards Robust Graph Incremental Learning on Evolving Graphs
by: Su, Junwei, et al.
Published: (2024)

PRES: Toward Scalable Memory-Based Dynamic Graph Neural Networks
by: Su, Junwei, et al.
Published: (2024)

Towards Fast Stochastic Sampling in Diffusion Generative Models
by: Pandey, Kushagra, et al.
Published: (2024)

Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
by: Arriola, Marianne, et al.
Published: (2025)

Joint Relational Database Generation via Graph-Conditional Diffusion Models
by: Ketata, Mohamed Amine, et al.
Published: (2025)

Communication-efficient Federated Graph Classification via Generative Diffusion Modeling
by: Wang, Xiuling, et al.
Published: (2026)

Diffusion-DFL: Decision-focused Diffusion Models for Stochastic Optimization
by: Zhao, Zihao, et al.
Published: (2025)

Stochastic Schrödinger Diffusion Models for Pure-State Ensemble Generation
by: Xu, Jian, et al.
Published: (2026)

Improving Reasoning for Diffusion Language Models via Group Diffusion Policy Optimization
by: Rojas, Kevin, et al.
Published: (2025)

TrajDLM: Topology-Aware Block Diffusion Language Model for Trajectory Generation
by: Wongso, Wilson, et al.
Published: (2026)

Stochastic Runge-Kutta Methods: Provable Acceleration of Diffusion Models
by: Wu, Yuchen, et al.
Published: (2024)

Graph Signal Generative Diffusion Models
by: Uslu, Yigit Berkay, et al.
Published: (2025)

Stochastic Diffusion: A Diffusion Probabilistic Model for Stochastic Time Series Forecasting
by: Liu, Yuansan, et al.
Published: (2024)

Heterogeneous Multi-agent Multi-armed Bandits on Stochastic Block Models
by: Xu, Mengfan, et al.
Published: (2025)

BG-HGNN: Toward Efficient Learning for Complex Heterogeneous Graphs
by: Su, Junwei, et al.
Published: (2024)

Fast Graph Generation via Spectral Diffusion
by: Luo, Tianze, et al.
Published: (2022)

RISSOLE: Parameter-efficient Diffusion Models via Block-wise Generation and Retrieval-Guidance
by: Mukherjee, Avideep, et al.
Published: (2024)

Graph Generation with Diffusion Mixture
by: Jo, Jaehyeong, et al.
Published: (2023)

Graph Attention is Not Always Beneficial: A Theoretical Analysis of Graph Attention Mechanisms via Contextual Stochastic Block Models
by: Ma, Zhongtian, et al.
Published: (2024)

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models
by: Komanduri, Aneesh, et al.
Published: (2024)

Hyperbolic Geometric Latent Diffusion Model for Graph Generation
by: Fu, Xingcheng, et al.
Published: (2024)

JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation
by: Shi, Ji, et al.
Published: (2025)

Graph Representation Learning with Diffusion Generative Models
by: Wesego, Daniel
Published: (2025)

Three Forms of Stochastic Injection for Improved Distribution-to-Distribution Generative Modeling
by: Su, Shiye, et al.
Published: (2025)

Graffe: Graph Representation Learning via Diffusion Probabilistic Models
by: Chen, Dingshuo, et al.
Published: (2025)

Graph Neural Diffusion via Generalized Opinion Dynamics
by: Hevapathige, Asela, et al.
Published: (2025)

Adaptive Diffusion Guidance via Stochastic Optimal Control
by: Azangulov, Iskander, et al.
Published: (2025)

SymDiff: Equivariant Diffusion via Stochastic Symmetrisation
by: Zhang, Leo, et al.
Published: (2024)

Break the Block: Dynamic-size Reasoning Blocks for Diffusion Large Language Models via Monotonic Entropy Descent with Reinforcement Learning
by: Jiang, Yan, et al.
Published: (2026)