3 citations · 3 across the 4 of their papers we have counts for
4 papers · 1 filter
ITSY: Causal Discovery From Irregular Time-Series Data
Wenbo Xu, Yue He, Yunhai Wang +2
Structural causal models for time series recover contemporaneous and lagged effects, but most methods require complete observation windows and become misspecified when samples are…
A Knowledge-Informed Pretrained Model for Causal Discovery
Wenbo Xu, Yue He, Yunhai Wang +4
Causal discovery has been widely studied, yet many existing methods rely on strong assumptions or fall into two extremes: either depending on costly interventional signals or parti…
Environment Inference for Learning Generalizable Dynamical System
Shixuan Liu, Yue He, Haotian Wang +4
Data-driven methods offer efficient and robust solutions for analyzing complex dynamical systems but rely on the assumption of I.I.D. data, driving the development of generalizatio…
LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence
Xingxuan Zhang, Gang Ren, Han Yu +35
We argue that progress toward general intelligence requires complementary foundation models grounded in language, the physical world, and structured data. This report presents Limi…