17 citations · 17 across the 6 of their papers we have counts for
6 papers
NUM2EVENT: Interpretable Event Reasoning from Numerical time-series
Ninghui Feng, Yiyan Qi
Large language models (LLMs) have recently demonstrated impressive multimodal reasoning capabilities, yet their understanding of purely numerical time-series signals remains limite…
IMTS is Worth Time Channel Patches: Visual Masked Autoencoders for Irregular Multivariate Time Series Prediction
Zhangyi Hu, Jiemin Wu, Hua Xu +5
Irregular Multivariate Time Series (IMTS) forecasting is challenging due to the unaligned nature of multi-channel signals and the prevalence of extensive missing data. Existing met…
Towards Reliable Time Series Forecasting under Future Uncertainty: Ambiguity and Novelty Rejection Mechanisms
Ninghui Feng, Songning Lai, Xin Zhou +9
In real-world time series forecasting, uncertainty and lack of reliable evaluation pose significant challenges. Notably, forecasting errors often arise from underfitting in-distrib…
DRIVE: Dependable Robust Interpretable Visionary Ensemble Framework in Autonomous Driving
Songning Lai, Tianlang Xue, Hongru Xiao +7
Recent advancements in autonomous driving have seen a paradigm shift towards end-to-end learning paradigms, which map sensory inputs directly to driving actions, thereby enhancing…
TimeSieve: Extracting Temporal Dynamics through Information Bottlenecks
Ninghui Feng, Songning Lai, Jiayu Yang +3
Time series forecasting has become an increasingly popular research area due to its critical applications in various real-world domains such as traffic management, weather predicti…
FTS: A Framework to Find a Faithful TimeSieve
Songning Lai, Ninghui Feng, Haochen Sui +5
The field of time series forecasting has garnered significant attention in recent years, prompting the development of advanced models like TimeSieve, which demonstrates impressive…