1 code implementation • 17 May 2024 • Zheng Dong, Renhe Jiang, Haotian Gao, Hangchen Liu, Jinliang Deng, Qingsong Wen, Xuan Song
Spatiotemporal time series forecasting plays a key role in a wide range of real-world applications.
1 code implementation • 1 Dec 2023 • Haotian Gao, Renhe Jiang, Zheng Dong, Jinliang Deng, Yuxin Ma, Xuan Song
Spatiotemporal forecasting techniques are significant for various domains such as transportation, energy, and weather.
Ranked #1 on Traffic Prediction on PEMS-BAY (using extra training data)
1 code implementation • 21 Aug 2023 • Hangchen Liu, Zheng Dong, Renhe Jiang, Jiewen Deng, Jinliang Deng, Quanjun Chen, Xuan Song
With the rapid development of the Intelligent Transportation System (ITS), accurate traffic forecasting has emerged as a critical challenge.
Ranked #1 on Traffic Prediction on PeMSD7
no code implementations • 20 Jun 2023 • Zheng Dong, Matthew Repasky, Xiuyuan Cheng, Yao Xie
Point process models are widely used for continuous asynchronous event data, where each data point includes time and additional information called "marks", which can be locations, nodes, or event types.
no code implementations • 21 May 2023 • Zheng Dong, Zekai Fan, Shixiang Zhu
To address this challenge, this study proposes a novel event-generation framework for modeling point processes with high-dimensional marks.
no code implementations • 21 Nov 2022 • Zheng Dong, Xiuyuan Cheng, Yao Xie
Another popular type of deep model for point process data is based on representing the influence kernel (rather than the intensity function) by neural networks.
1 code implementation • 23 Oct 2022 • Chengyin Li, Zheng Dong, Nathan Fisher, Dongxiao Zhu
Electric Vehicle (EV) charging recommendation that both accommodates user preference and adapts to the ever-changing external environment arises as a cost-effective strategy to alleviate the range anxiety of private EV drivers.
no code implementations • 3 Dec 2021 • Zheng Dong, Ke Xu, Ziheng Duan, Hujun Bao, Weiwei Xu, Rynson W. H. Lau
Our key idea is to exploit the complementary properties of depth denoising and 3D reconstruction, for learning a two-scale PIFu representation to reconstruct high-frequency facial details and consistent bodies separately.
1 code implementation • NeurIPS 2021 • Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, HengShu Zhu, Hui Xiong
To this end, in this paper, we revisit the task of topic modeling by transforming each document into a directed graph with word dependency as edges between word nodes, and develop a novel approach, namely Graph Neural Topic Model (GNTM).
1 code implementation • ICLR 2022 • Shixiang Zhu, Haoyun Wang, Zheng Dong, Xiuyuan Cheng, Yao Xie
In this paper, we introduce a novel and general neural network-based non-stationary influence kernel with high expressiveness for handling complex discrete events data while providing theoretical performance guarantees.
1 code implementation • ICCV 2021 • Zheng Dong, Ke Xu, Yin Yang, Hujun Bao, Weiwei Xu, Rynson W. H. Lau
It is beneficial to strong reflection detection and substantially improves the quality of reflection removal results.
no code implementations • 6 Jan 2020 • Guangmo Tong, Ruiqi Wang, Chen Ling, Zheng Dong, Xiang Li
The well-known influence maximization problem aims at maximizing the influence of one information cascade in a social network by selecting appropriate seed users prior to the diffusion process.
Social and Information Networks