9 citations · 23 across the 6 of their papers we have counts for
7 papers · 1 filter
Decorrelating the Future: Joint Frequency Domain Learning for Spatio-temporal Forecasting
Zepu Wang, Bowen Liao, Jeff +1
Standard direct forecasting models typically rely on point-wise objectives such as Mean Squared Error, which fail to capture the complex spatio-temporal dependencies inherent in gr…
Domain Adaptation Framework for Turning Movement Count Estimation with Limited Data
Xiaobo Ma, Hyunsoo Noh, Ryan Hatch +2
Urban transportation networks are vital for the efficient movement of people and goods, necessitating effective traffic management and planning. An integral part of traffic managem…
Data-Driven Transfer Learning Framework for Estimating Turning Movement Counts
Xiaobo Ma, Hyunsoo Noh, Ryan Hatch +2
Urban transportation networks are vital for the efficient movement of people and goods, necessitating effective traffic management and planning. An integral part of traffic managem…
Uncertainty-Aware Crime Prediction With Spatial Temporal Multivariate Graph Neural Networks
Zepu Wang, Xiaobo Ma, Huajie Yang +3
Crime forecasting is a critical component of urban analysis and essential for stabilizing society today. Unlike other time series forecasting problems, crime incidents are sparse,…
Unlocking the Power of LSTM for Long Term Time Series Forecasting
Yaxuan Kong, Zepu Wang, Yuqi Nie +5
Traditional recurrent neural network architectures, such as long short-term memory neural networks (LSTM), have historically held a prominent role in time series forecasting (TSF)…
TSI-Bench: Benchmarking Time Series Imputation
Wenjie Du, Jun Wang, Linglong Qian +12
Effective imputation is a crucial preprocessing step for time series analysis. Despite the development of numerous deep learning algorithms for time series imputation, the communit…
Large Language Models for Mobility Analysis in Transportation Systems: A Survey on Forecasting Tasks
Zijian Zhang, Yujie Sun, Zepu Wang +5
Mobility analysis is a crucial element in the research area of transportation systems. Forecasting traffic information offers a viable solution to address the conflict between incr…