24 citations · 28 across the 5 of their papers we have counts for
8 papers
TimeES: Probabilistic and Deterministic Time Series Forecasting via Evolutionary Spectra
Weiwei Ye, Renhe Jiang, Hangchen Liu +2
Real-world time series are inherently non-stationary, with trends, periodic patterns, and uncertainty evolving over time. While the Fourier domain offers a natural lens to model ti…
DiffPTS: Rethinking Diffusion ELBO for Probabilistic Time Series Forecasting
Weiwei Ye, Dongyuan Li, Hangchen Liu +3
Probabilistic time series forecasting requires modeling and predicting complex and time-varying distributions. Recently, Denoising Diffusion Probabilistic Model (DDPM)-based approa…
NumericJev: Jev-like LLM Numerical Decoding with Multiway Decision Trees
Weiwei Ye, Hangchen Liu, Renhe Jiang
Large language models can interpret natural lan- guage, yet robust decisions remain challenging. Jev-like models expose structured choices, but these interfaces do not directly pro…
BrainLinear: A Linear Model for Brain Network Analysis in Sparse Tangent Subspaces
Sijing Wu, Dongyuan Li, Miaoting Huang +4
Functional connectome analysis examines brain-region interactions to understand and identify disorders such as autism spectrum disorder and Alzheimer's disease. Existing methods ty…
TimeClaw: A Time-Series AI Agent with Exploratory Execution Learning
Hangchen Liu, Dongyuan Li, Renhe Jiang +3
Time series analysis underpins forecasting, monitoring, and decision making in domains such as finance and weather, where solving a task often requires both numerical accuracy and…
Non-stationary Diffusion For Probabilistic Time Series Forecasting
Weiwei Ye, Zhuopeng Xu, Ning Gui
Due to the dynamics of underlying physics and external influences, the uncertainty of time series often varies over time. However, existing Denoising Diffusion Probabilistic Models…
Frequency Adaptive Normalization For Non-stationary Time Series Forecasting
Weiwei Ye, Songgaojun Deng, Qiaosha Zou +1
Time series forecasting typically needs to address non-stationary data with evolving trend and seasonal patterns. To address the non-stationarity, reversible instance normalization…
Data Imputation with Iterative Graph Reconstruction
Jiajun Zhong, Weiwei Ye, Ning Gui
Effective data imputation demands rich latent ``structure" discovery capabilities from ``plain" tabular data. Recent advances in graph neural networks-based data imputation solutio…