2 citations · 5 across the 10 of their papers we have counts for
10 papers
Frequency Enhanced Pre-training for Cross-city Few-shot Traffic Forecasting
Zhanyu Liu, Jianrong Ding, Guanjie Zheng
The field of Intelligent Transportation Systems (ITS) relies on accurate traffic forecasting to enable various downstream applications. However, developing cities often face challe…
MagiNet: Mask-Aware Graph Imputation Network for Incomplete Traffic Data
Jianping Zhou, Bin Lu, Zhanyu Liu +6
Due to detector malfunctions and communication failures, missing data is ubiquitous during the collection of traffic data. Therefore, it is of vital importance to impute the missin…
CMamba: Channel Correlation Enhanced State Space Models for Multivariate Time Series Forecasting
Chaolv Zeng, Zhanyu Liu, Guanjie Zheng +1
Recent advancements in multivariate time series forecasting have been propelled by Linear-based, Transformer-based, and Convolution-based models, with Transformer-based architectur…
CondTSF: One-line Plugin of Dataset Condensation for Time Series Forecasting
Jianrong Ding, Zhanyu Liu, Guanjie Zheng +2
Dataset condensation is a newborn technique that generates a small dataset that can be used in training deep neural networks to lower training costs. The objective of dataset conde…
Graph Data Condensation via Self-expressive Graph Structure Reconstruction
Zhanyu Liu, Chaolv Zeng, Guanjie Zheng
With the increasing demands of training graph neural networks (GNNs) on large-scale graphs, graph data condensation has emerged as a critical technique to relieve the storage and t…
Dataset Condensation for Time Series Classification via Dual Domain Matching
Zhanyu Liu, Ke Hao, Guanjie Zheng +1
Time series data has been demonstrated to be crucial in various research fields. The management of large quantities of time series data presents challenges in terms of deep learnin…
Multi-scale Traffic Pattern Bank for Cross-city Few-shot Traffic Forecasting
Zhanyu Liu, Guanjie Zheng, Yanwei Yu
Traffic forecasting is crucial for intelligent transportation systems (ITS), aiding in efficient resource allocation and effective traffic control. However, its effectiveness often…
Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank
Zhanyu Liu, Guanjie Zheng, Yanwei Yu
Traffic forecasting is a critical service in Intelligent Transportation Systems (ITS). Utilizing deep models to tackle this task relies heavily on data from traffic sensors or vehi…
FDTI: Fine-grained Deep Traffic Inference with Roadnet-enriched Graph
Zhanyu Liu, Chumeng Liang, Guanjie Zheng +1
This paper proposes the fine-grained traffic prediction task (e.g. interval between data points is 1 minute), which is essential to traffic-related downstream applications. Under t…
CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulation
Chumeng Liang, Zherui Huang, Yicheng Liu +7
Traffic simulation provides interactive data for the optimization of traffic control policies. However, existing traffic simulators are limited by their lack of scalability and sho…