DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models-Reference-Cited by-同舟云学术

DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models

Published:2023-11-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems
language:
Short-container-title:

Author:

Wen Haomin¹^ORCID,Lin Youfang²^ORCID,Xia Yutong³^ORCID,Wan Huaiyu¹^ORCID,Wen Qingsong⁴^ORCID,Zimmermann Roger³^ORCID,Liang Yuxuan⁵^ORCID

Affiliation:

1. Beijing Jiaotong University - China;, Beijing, China

2. Beijing Jiaotong University - Beijing - China, Beijing, China

3. School of Computing - National University of Singapore - Singapore, Singapore, Singapore

4. DAMO Academy - Alibaba Group, Hangzhou, China

5. Hong Kong University of Science and Technology (Guangzhou), Guangzhou, China

Funder

Guangzhou Municiple Science and Technology Project

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3589132.3625614

Reference54 articles.

1. Shaojie Bai , J Zico Kolter , and Vladlen Koltun . 2018. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 ( 2018 ). Shaojie Bai, J Zico Kolter, and Vladlen Koltun. 2018. An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 (2018).

2. Ping Chang , Huayu Li , Stuart F Quan , Janet Roveda , and Ao Li . 2023 . TDSTF: Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting. arXiv preprint arXiv:2301.06625 (2023). Ping Chang, Huayu Li, Stuart F Quan, Janet Roveda, and Ao Li. 2023. TDSTF: Transformer-based Diffusion probabilistic model for Sparse Time series Forecasting. arXiv preprint arXiv:2301.06625 (2023).

3. Zhengping Che , Sanjay Purushotham , Kyunghyun Cho , David Sontag , and Yan Liu . 2018. Recurrent neural networks for multivariate time series with missing values. Scientific reports 8, 1 ( 2018 ), 6085. Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David Sontag, and Yan Liu. 2018. Recurrent neural networks for multivariate time series with missing values. Scientific reports 8, 1 (2018), 6085.

4. Nanxin Chen , Yu Zhang , Heiga Zen , Ron J Weiss , Mohammad Norouzi , and William Chan . 2020 . WaveGrad: Estimating Gradients for Waveform Generation. In International Conference on Learning Representations. Nanxin Chen, Yu Zhang, Heiga Zen, Ron J Weiss, Mohammad Norouzi, and William Chan. 2020. WaveGrad: Estimating Gradients for Waveform Generation. In International Conference on Learning Representations.

5. Weiqi Chen Wenwei Wang Bingqing Peng Qingsong Wen Tian Zhou and Liang Sun. 2022. Learning to rotate: Quaternion transformer for complicated periodical time series forecasting. In KDD. 146--156. Weiqi Chen Wenwei Wang Bingqing Peng Qingsong Wen Tian Zhou and Liang Sun. 2022. Learning to rotate: Quaternion transformer for complicated periodical time series forecasting. In KDD. 146--156.

Cited by 13 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook;Information Fusion;2025-01

2. CAG-NSPDE: Continuous adaptive graph neural stochastic partial differential equations for traffic flow forecasting;Neurocomputing;2024-10

3. Self-Supervised Learning for Time Series Analysis: Taxonomy, Progress, and Prospects;IEEE Transactions on Pattern Analysis and Machine Intelligence;2024-10

4. LaDe: The First Comprehensive Last-mile Express Dataset from Industry;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

5. Foundation Models for Time Series Analysis: A Tutorial and Survey;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24