Search Results for author: Leilei Sun

Found 26 papers, 21 papers with code

Regions are Who Walk Them: a Large Pre-trained Spatiotemporal Model Based on Human Mobility for Ubiquitous Urban Sensing

1 code implementation17 Nov 2023 Ruixing Zhang, Liangzhe Han, Leilei Sun, Yunqi Liu, Jibin Wang, Weifeng Lv

To tap into the rich information within population movement, based on the perspective that Regions Are Who walk them, we propose a large spatiotemporal model based on trajectories (RAW).

Pretraining Language Models with Text-Attributed Heterogeneous Graphs

1 code implementation19 Oct 2023 Tao Zou, Le Yu, Yifei HUANG, Leilei Sun, Bowen Du

In many real-world scenarios (e. g., academic networks, social platforms), different types of entities are not only associated with texts but also connected by various relationships, which can be abstracted as Text-Attributed Heterogeneous Graphs (TAHGs).

Link Prediction Node Classification +1

Self-optimizing Feature Generation via Categorical Hashing Representation and Hierarchical Reinforcement Crossing

1 code implementation8 Sep 2023 Wangyang Ying, Dongjie Wang, Kunpeng Liu, Leilei Sun, Yanjie Fu

Feature generation aims to generate new and meaningful features to create a discriminative representation space. A generated feature is meaningful when the generated feature is from a feature pair with inherent feature interaction.

Descriptive

Adaptive Taxonomy Learning and Historical Patterns Modelling for Patent Classification

1 code implementation10 Aug 2023 Tao Zou, Le Yu, Leilei Sun, Bowen Du, Deqing Wang, Fuzhen Zhuang

Finally, we combine the contextual information of patent texts that contains the semantics of IPC codes, and assignees' sequential preferences to make predictions.

Classification

Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction

1 code implementation4 Aug 2023 Tao Zou, Le Yu, Leilei Sun, Bowen Du, Deqing Wang, Fuzhen Zhuang

Finally, the patent application trend is predicted by aggregating the representations of the target company and classification codes from static, dynamic, and hierarchical perspectives.

Classification Graph Learning +1

Learning Joint 2D & 3D Diffusion Models for Complete Molecule Generation

2 code implementations21 May 2023 Han Huang, Leilei Sun, Bowen Du, Weifeng Lv

To capture the correlation between molecular graphs and geometries in the diffusion process, we develop a Diffusion Graph Transformer to parameterize the data prediction model that recovers the original data from noisy data.

3D Molecule Generation Drug Discovery +2

PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation

1 code implementation20 Feb 2023 Mingzhe Liu, Han Huang, Hao Feng, Leilei Sun, Bowen Du, Yanjie Fu

Our proposed framework provides a conditional feature extraction module first to extract the coarse yet effective spatiotemporal dependencies from conditional information as the global context prior.

Imputation Noise Estimation

Conditional Diffusion Based on Discrete Graph Structures for Molecular Graph Generation

1 code implementation1 Jan 2023 Han Huang, Leilei Sun, Bowen Du, Weifeng Lv

To accomplish these goals, we propose a novel Conditional Diffusion model based on discrete Graph Structures (CDGS) for molecular graph generation.

Drug Discovery Graph Generation +2

Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning

no code implementations1 Dec 2022 Dongjie Wang, Lingfei Wu, Denghui Zhang, Jingbo Zhou, Leilei Sun, Yanjie Fu

The third stage is to leverage multi-attentions to model the zone-zone peer dependencies of the functionality projections to generate grid-level land-use configurations.

Automated Urban Planning aware Spatial Hierarchies and Human Instructions

no code implementations26 Sep 2022 Dongjie Wang, Kunpeng Liu, Yanyong Huang, Leilei Sun, Bowen Du, Yanjie Fu

While automated urban planners have been examined, they are constrained because of the following: 1) neglecting human requirements in urban planning; 2) omitting spatial hierarchies in urban planning, and 3) lacking numerous urban plan data samples.

Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction

1 code implementation30 Jun 2022 Liangzhe Han, Xiaojian Ma, Leilei Sun, Bowen Du, Yanjie Fu, Weifeng Lv, Hui Xiong

Traffic demand forecasting by deep neural networks has attracted widespread interest in both academia and industry society.

Graph Representation Learning

Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting

1 code implementation28 Jun 2022 Junchen Ye, Zihan Liu, Bowen Du, Leilei Sun, Weimiao Li, Yanjie Fu, Hui Xiong

To equip the graph neural network with a flexible and practical graph structure, in this paper, we investigate how to model the evolutionary and multi-scale interactions of time series.

Multivariate Time Series Forecasting Self-Learning +1

Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction

1 code implementation29 May 2022 Ruixing Zhang, Liangzhe Han, Boyi Liu, Jiayuan Zeng, Leilei Sun

Last, an objective function is designed to derive the future OD demands according to the most recent node representations, and also to tackle the data sparsity problem in OD prediction.

Graph Learning Graph Representation Learning

Exploiting Global and Local Hierarchies for Hierarchical Text Classification

1 code implementation5 May 2022 Ting Jiang, Deqing Wang, Leilei Sun, Zhongzhi Chen, Fuzhen Zhuang, Qinghong Yang

Existing methods encode label hierarchy in a global view, where label hierarchy is treated as the static hierarchical structure containing all labels.

Multi Label Text Classification Multi-Label Text Classification +1

Continuous-Time User Preference Modelling for Temporal Sets Prediction

1 code implementation12 Apr 2022 Le Yu, Zihang Liu, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv

Previous studies for temporal sets prediction mainly focus on the modelling of elements and implicitly represent each user's preference based on his/her interacted elements.

Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning

no code implementations12 Oct 2021 Dongjie Wang, Kunpeng Liu, Pauline Johnson, Leilei Sun, Bowen Du, Yanjie Fu

Existing studies usually ignore the need of personalized human guidance in planning, and spatial hierarchical structure in planning generation.

Image Generation

Analysis for full face mechanical behaviors through spatial deduction model with real-time monitoring data

no code implementations27 Sep 2021 Xuyan Tan, Yuhang Wang, Bowen Du, Junchen Ye, Weizhong Chen, Leilei Sun, Liping Li

Mechanical analysis for the full face of tunnel structure is crucial to maintain stability, which is a challenge in classical analytical solutions and data analysis.

Heterogeneous Graph Representation Learning with Relation Awareness

1 code implementation24 May 2021 Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv, Hui Xiong

Moreover, a semantic fusing module is presented to aggregate relation-aware node representations into a compact representation with the learned relation representations.

Graph Learning Graph Representation Learning +4

LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification

1 code implementation9 Jan 2021 Ting Jiang, Deqing Wang, Leilei Sun, Huayi Yang, Zhengyang Zhao, Fuzhen Zhuang

In LightXML, we use generative cooperative networks to recall and rank labels, in which label recalling part generates negative and positive labels, and label ranking part distinguishes positive labels from these labels.

General Classification Multi Label Text Classification +2

Hybrid Micro/Macro Level Convolution for Heterogeneous Graph Learning

1 code implementation29 Dec 2020 Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Weifeng Lv, Hui Xiong

Representation learning on heterogeneous graphs aims to obtain low-dimensional node representations that could preserve both node attributes and relation information.

Graph Learning Node Property Prediction +1

Coupled Layer-wise Graph Convolution for Transportation Demand Prediction

1 code implementation15 Dec 2020 Junchen Ye, Leilei Sun, Bowen Du, Yanjie Fu, Hui Xiong

Graph Convolutional Network (GCN) has been widely applied in transportation demand prediction due to its excellent ability to capture non-Euclidean spatial dependence among station-level or regional transportation demands.

Defending Water Treatment Networks: Exploiting Spatio-temporal Effects for Cyber Attack Detection

no code implementations26 Aug 2020 Dongjie Wang, Pengyang Wang, Jingbo Zhou, Leilei Sun, Bowen Du, Yanjie Fu

To this end, we propose a structured anomaly detection framework to defend WTNs by modeling the spatio-temporal characteristics of cyber attacks in WTNs.

Anomaly Detection Attribute +2

Predicting Temporal Sets with Deep Neural Networks

2 code implementations20 Jun 2020 Le Yu, Leilei Sun, Bowen Du, Chuanren Liu, Hui Xiong, Weifeng Lv

Given a sequence of sets, where each set contains an arbitrary number of elements, the problem of temporal sets prediction aims to predict the elements in the subsequent set.

Time Series Analysis

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