6 papers
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…
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…
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…
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…
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…