163 citations · 576 across the 33 of their papers we have counts for
10 papers · 1 filter
Fitting Unknown Number of Hyperplanes with Manifold Optimization
Zhiqin Cheng, Yu Zhan, Mingjin Zhang +2
Fitting an unknown number of hyperplanes to data is a fundamental yet challenging problem in machine learning, characterized by its non-convexity, non-differentiability, and unknow…
Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction
Guangyin Jin, Lingbo Liu, Fuxian Li +1
Traffic congestion event prediction is an important yet challenging task in intelligent transportation systems. Many existing works about traffic prediction integrate various tempo…
Long-term Wind Power Forecasting with Hierarchical Spatial-Temporal Transformer
Yang Zhang, Lingbo Liu, Xinyu Xiong +3
Wind power is attracting increasing attention around the world due to its renewable, pollution-free, and other advantages. However, safely and stably integrating the high permeabil…
Road Network Guided Fine-Grained Urban Traffic Flow Inference
Lingbo Liu, Mengmeng Liu, Guanbin Li +3
Accurate inference of fine-grained traffic flow from coarse-grained one is an emerging yet crucial problem, which can help greatly reduce the number of the required traffic monitor…
Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation
Lingbo Liu, Yuying Zhu, Guanbin Li +3
Metro origin-destination prediction is a crucial yet challenging time-series analysis task in intelligent transportation systems, which aims to accurately forecast two specific typ…
Physical-Virtual Collaboration Modeling for Intra-and Inter-Station Metro Ridership Prediction
Lingbo Liu, Jingwen Chen, Hefeng Wu +3
Due to the widespread applications in real-world scenarios, metro ridership prediction is a crucial but challenging task in intelligent transportation systems. However, conventiona…
Dynamic Spatial-Temporal Representation Learning for Traffic Flow Prediction
Lingbo Liu, Jiajie Zhen, Guanbin Li +4
As a crucial component in intelligent transportation systems, traffic flow prediction has recently attracted widespread research interest in the field of artificial intelligence (A…
Investigation of wind pressures on tall building under interference effects using machine learning techniques
Gang Hu, Lingbo Liu, Dacheng Tao +2
Interference effects of tall buildings have attracted numerous studies due to the boom of clusters of tall buildings in megacities. To fully understand the interference effects of…
Contextualized Spatial-Temporal Network for Taxi Origin-Destination Demand Prediction
Lingbo Liu, Zhilin Qiu, Guanbin Li +3
Taxi demand prediction has recently attracted increasing research interest due to its huge potential application in large-scale intelligent transportation systems. However, most of…
Attentive Crowd Flow Machines
Lingbo Liu, Ruimao Zhang, Jiefeng Peng +3
Traffic flow prediction is crucial for urban traffic management and public safety. Its key challenges lie in how to adaptively integrate the various factors that affect the flow ch…