1 citations · 1 across the 4 of their papers we have counts for
8 papers
GenTS: A Comprehensive Benchmark Library for Generative Time Series Models
Chenxi Wang, Xiaorong Wang, Peiyang Li +1
Generative models have demonstrated remarkable potential in time series analysis tasks, like synthesis, forecasting, imputation, etc. However, offering limited coverage for generat…
Task-oriented Time Series Imputation Evaluation via Generalized Representers
Zhixian Wang, Linxiao Yang, Liang Sun +2
Time series analysis is widely used in many fields such as power energy, economics, and transportation, including different tasks such as forecasting, anomaly detection, classifica…
Evolving Multi-Scale Normalization for Time Series Forecasting under Distribution Shifts
Dalin Qin, Yehui Li, Weiqi Chen +5
Complex distribution shifts are the main obstacle to achieving accurate long-term time series forecasting. Several efforts have been conducted to capture the distribution character…
A Survey on Diffusion Models for Time Series and Spatio-Temporal Data
Yiyuan Yang, Ming Jin, Haomin Wen +9
Diffusion models have been widely used in time series and spatio-temporal data, enhancing generative, inferential, and downstream capabilities. These models are applied across dive…
Explaining Time Series via Contrastive and Locally Sparse Perturbations
Zichuan Liu, Yingying Zhang, Tianchun Wang +8
Explaining multivariate time series is a compound challenge, as it requires identifying important locations in the time series and matching complex temporal patterns. Although prev…
HiMTM: Hierarchical Multi-Scale Masked Time Series Modeling with Self-Distillation for Long-Term Forecasting
Shubao Zhao, Ming Jin, Zhaoxiang Hou +4
Time series forecasting is a critical and challenging task in practical application. Recent advancements in pre-trained foundation models for time series forecasting have gained si…