Search Results for author: Bowen Du

Found 27 papers, 19 papers with code

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

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.


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

Fleet Rebalancing for Expanding Shared e-Mobility Systems: A Multi-agent Deep Reinforcement Learning Approach

1 code implementation11 Nov 2022 Man Luo, Bowen Du, Wenzhe Zhang, Tianyou Song, Kun Li, HongMing Zhu, Mark Birkin, Hongkai Wen

This is particularly challenging in the context of expanding systems, because i) the range of the EVs is limited while charging time is typically long, which constrain the viable rebalancing operations; and ii) the EV stations in the system are dynamically changing, i. e., the legitimate targets for rebalancing operations can vary over time.

Multi-agent Reinforcement Learning

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

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.

Deployment Optimization for Shared e-Mobility Systems with Multi-agent Deep Neural Search

no code implementations3 Nov 2021 Man Luo, Bowen Du, Konstantin Klemmer, HongMing Zhu, Hongkai Wen

Shared e-mobility services have been widely tested and piloted in cities across the globe, and already woven into the fabric of modern urban planning.

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 +3

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 Cyber Attack Detection +1

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

Snoopy: Sniffing Your Smartwatch Passwords via Deep Sequence Learning

1 code implementation10 Dec 2019 Chris Xiaoxuan Lu, Bowen Du, Hongkai Wen, Sen Wang, Andrew Markham, Ivan Martinovic, Yiran Shen, Niki Trigoni

Demand for smartwatches has taken off in recent years with new models which can run independently from smartphones and provide more useful features, becoming first-class mobile platforms.

Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction

2 code implementations2 Sep 2019 Lingbo Liu, Jiajie Zhen, Guanbin Li, Geng Zhan, Zhaocheng He, Bowen Du, Liang Lin

Specifically, the first ConvLSTM unit takes normal traffic flow features as input and generates a hidden state at each time-step, which is further fed into the connected convolutional layer for spatial attention map inference.

Representation Learning Traffic Prediction

Autonomous Learning for Face Recognition in the Wild via Ambient Wireless Cues

1 code implementation14 Aug 2019 Chris Xiaoxuan Lu, Xuan Kan, Bowen Du, Changhao Chen, Hongkai Wen, Andrew Markham, Niki Trigoni, John Stankovic

Inspired by the fact that most people carry smart wireless devices with them, e. g. smartphones, we propose to use this wireless identifier as a supervisory label.

Face Recognition

Demand Prediction for Electric Vehicle Sharing

no code implementations10 Mar 2019 Man Luo, Hongkai Wen, Yi Luo, Bowen Du, Konstantin Klemmer, Hong-Ming Zhu

Electric Vehicle (EV) sharing systems have recently experienced unprecedented growth across the globe.

Decision Making

Attentive Crowd Flow Machines

no code implementations1 Sep 2018 Lingbo Liu, Ruimao Zhang, Jiefeng Peng, Guanbin Li, Bowen Du, Liang Lin

Traffic flow prediction is crucial for urban traffic management and public safety.


S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension

no code implementations15 Jun 2017 Chuanqi Tan, Furu Wei, Nan Yang, Bowen Du, Weifeng Lv, Ming Zhou

We build the answer extraction model with state-of-the-art neural networks for single passage reading comprehension, and propose an additional task of passage ranking to help answer extraction in multiple passages.

Answer Generation Machine Reading Comprehension +1

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