Latent Conditional Diffusion-based Data Augmentation for Continuous-Time Dynamic Graph Model
Fuente:
arXiv
Guardado en:
| Autores principales: | Tian, Yuxing, Qi, Yiyan, Jiang, Aiwen, Huang, Qi, Guo, Jian |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
por: Tian, Yuxing, et al.
Publicado: (2026)
por: Tian, Yuxing, et al.
Publicado: (2026)
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making
por: Guo, Jian, et al.
Publicado: (2024)
por: Guo, Jian, et al.
Publicado: (2024)
Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data
por: Leung, Cheuk Hang, et al.
Publicado: (2025)
por: Leung, Cheuk Hang, et al.
Publicado: (2025)
Structure-based RNA Design by Step-wise Optimization of Latent Diffusion Model
por: Si, Qi, et al.
Publicado: (2026)
por: Si, Qi, et al.
Publicado: (2026)
MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training
por: Chen, Zhanpeng, et al.
Publicado: (2024)
por: Chen, Zhanpeng, et al.
Publicado: (2024)
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
por: Huang, Yiyan, et al.
Publicado: (2024)
por: Huang, Yiyan, et al.
Publicado: (2024)
Latent-Augmented Discrete Diffusion Models
por: Shariatian, Dario, et al.
Publicado: (2025)
por: Shariatian, Dario, et al.
Publicado: (2025)
Reinforcement Learning with Euclidean Data Augmentation for State-Based Continuous Control
por: Luo, Jinzhu, et al.
Publicado: (2024)
por: Luo, Jinzhu, et al.
Publicado: (2024)
NUM2EVENT: Interpretable Event Reasoning from Numerical time-series
por: Feng, Ninghui, et al.
Publicado: (2025)
por: Feng, Ninghui, et al.
Publicado: (2025)
Democratizing Large Language Model-Based Graph Data Augmentation via Latent Knowledge Graphs
por: Feng, Yushi, et al.
Publicado: (2025)
por: Feng, Yushi, et al.
Publicado: (2025)
Diff-MTS: Temporal-Augmented Conditional Diffusion-based AIGC for Industrial Time Series Towards the Large Model Era
por: Ren, Lei, et al.
Publicado: (2024)
por: Ren, Lei, et al.
Publicado: (2024)
FLAG: Foundation model representation with Latent diffusion Alignment via Graph for spatial gene expression prediction
por: Si, Qi, et al.
Publicado: (2026)
por: Si, Qi, et al.
Publicado: (2026)
Energy-Structured Low-Rank Adaptation for Continual Learning
por: Li, Longhua, et al.
Publicado: (2026)
por: Li, Longhua, et al.
Publicado: (2026)
Detecting High-Potential SMEs with Heterogeneous Graph Neural Networks
por: Qi, Yijiashun, et al.
Publicado: (2026)
por: Qi, Yijiashun, et al.
Publicado: (2026)
Latent Space Score-based Diffusion Model for Probabilistic Multivariate Time Series Imputation
por: Liang, Guojun, et al.
Publicado: (2024)
por: Liang, Guojun, et al.
Publicado: (2024)
CSPO: Cross-Market Synergistic Stock Price Movement Forecasting with Pseudo-volatility Optimization
por: Lin, Sida, et al.
Publicado: (2025)
por: Lin, Sida, et al.
Publicado: (2025)
Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift
por: Wang, Bohan, et al.
Publicado: (2024)
por: Wang, Bohan, et al.
Publicado: (2024)
Prompt-Driven Continual Graph Learning
por: Wang, Qi, et al.
Publicado: (2025)
por: Wang, Qi, et al.
Publicado: (2025)
Latent Diffusion : Multi-Dimension Stable Diffusion Latent Space Explorer
por: Zhong, Zhihua, et al.
Publicado: (2025)
por: Zhong, Zhihua, et al.
Publicado: (2025)
Retrieval Augmented Generation for Dynamic Graph Modeling
por: Wu, Yuxia, et al.
Publicado: (2024)
por: Wu, Yuxia, et al.
Publicado: (2024)
JTreeformer: Graph-Transformer via Latent-Diffusion Model for Molecular Generation
por: Shi, Ji, et al.
Publicado: (2025)
por: Shi, Ji, et al.
Publicado: (2025)
SwinGNN: Rethinking Permutation Invariance in Diffusion Models for Graph Generation
por: Yan, Qi, et al.
Publicado: (2023)
por: Yan, Qi, et al.
Publicado: (2023)
Seismic Acoustic Impedance Inversion Framework Based on Conditional Latent Generative Diffusion Model
por: Chen, Jie, et al.
Publicado: (2025)
por: Chen, Jie, et al.
Publicado: (2025)
KEPo: Knowledge Evolution Poison on Graph-based Retrieval-Augmented Generation
por: Chen, Qizhi, et al.
Publicado: (2026)
por: Chen, Qizhi, et al.
Publicado: (2026)
Goal-Conditioned Data Augmentation for Offline Reinforcement Learning
por: Huang, Xingshuai, et al.
Publicado: (2024)
por: Huang, Xingshuai, et al.
Publicado: (2024)
Text Diffusion with Reinforced Conditioning
por: Liu, Yuxuan, et al.
Publicado: (2024)
por: Liu, Yuxuan, et al.
Publicado: (2024)
On the Implicit Adversariality of Catastrophic Forgetting in Deep Continual Learning
por: Peng, Ze, et al.
Publicado: (2025)
por: Peng, Ze, et al.
Publicado: (2025)
Stabilizing Recurrent Dynamics for Test-Time Scalable Latent Reasoning in Looped Language Models
por: Yang, Xiao-Wen, et al.
Publicado: (2026)
por: Yang, Xiao-Wen, et al.
Publicado: (2026)
Diffusion and Flow Matching Models for Tabular Data: A Survey
por: Li, Zhong, et al.
Publicado: (2025)
por: Li, Zhong, et al.
Publicado: (2025)
Refining Alignment Framework for Diffusion Models with Intermediate-Step Preference Ranking
por: Ren, Jie, et al.
Publicado: (2025)
por: Ren, Jie, et al.
Publicado: (2025)
Model Merging in the Essential Subspace
por: Li, Longhua, et al.
Publicado: (2026)
por: Li, Longhua, et al.
Publicado: (2026)
Filling the Missings: Spatiotemporal Data Imputation by Conditional Diffusion
por: He, Wenying, et al.
Publicado: (2025)
por: He, Wenying, et al.
Publicado: (2025)
MemCast: Memory-Driven Time Series Forecasting with Experience-Conditioned Reasoning
por: Tao, Xiaoyu, et al.
Publicado: (2026)
por: Tao, Xiaoyu, et al.
Publicado: (2026)
DiLaDiff: Distilled Latent-Augmented Diffusion for Language Modeling
por: Lemercier, Jean-Marie, et al.
Publicado: (2026)
por: Lemercier, Jean-Marie, et al.
Publicado: (2026)
ReAttn: Improving Attention-based Re-ranking via Attention Re-weighting
por: Tian, Yuxing, et al.
Publicado: (2026)
por: Tian, Yuxing, et al.
Publicado: (2026)
Latent Laplace Diffusion for Irregular Multivariate Time Series
por: You, Zinuo, et al.
Publicado: (2026)
por: You, Zinuo, et al.
Publicado: (2026)
Exploring Molecule Generation Using Latent Space Graph Diffusion
por: Pombala, Prashanth, et al.
Publicado: (2025)
por: Pombala, Prashanth, et al.
Publicado: (2025)
A Time-Series Data Augmentation Model through Diffusion and Transformer Integration
por: Zhang, Yuren, et al.
Publicado: (2025)
por: Zhang, Yuren, et al.
Publicado: (2025)
Random Conditioning with Distillation for Data-Efficient Diffusion Model Compression
por: Kim, Dohyun, et al.
Publicado: (2025)
por: Kim, Dohyun, et al.
Publicado: (2025)
Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion
por: Nie, Tong, et al.
Publicado: (2025)
por: Nie, Tong, et al.
Publicado: (2025)
Ejemplares similares
-
Learning Discriminative and Generalizable Anomaly Detector for Dynamic Graph with Limited Supervision
por: Tian, Yuxing, et al.
Publicado: (2026) -
Guided Learning: Lubricating End-to-End Modeling for Multi-stage Decision-making
por: Guo, Jian, et al.
Publicado: (2024) -
Distributionally Robust Policy Evaluation and Learning for Continuous Treatment with Observational Data
por: Leung, Cheuk Hang, et al.
Publicado: (2025) -
Structure-based RNA Design by Step-wise Optimization of Latent Diffusion Model
por: Si, Qi, et al.
Publicado: (2026) -
MLLM Is a Strong Reranker: Advancing Multimodal Retrieval-augmented Generation via Knowledge-enhanced Reranking and Noise-injected Training
por: Chen, Zhanpeng, et al.
Publicado: (2024)