5 papers · 1 filter
Generative Bayesian Filtering for State Estimation
Lei Cao, Sihang Feng, Jixin Yan +2
The state of a dynamic system evolves over time, switching among several latent modes that govern its observable behavior. Filtering methods infer the latent state from observation…
LMT: A Bayesian Framework for Causal Discovery from Textual Alarm Records in Manufacturing Systems
Xiaofeng Xiao, Jianhong Chen, Qiuzhuang Sun +2
Textual event records, such as alarm logs, have become an increasingly common data source in engineering and manufacturing systems. Beyond identifying correlations or recurring pat…
Causal Discovery from Heteroscedastic Stochastic Dynamical Systems under Imperfect Physical Models
Jianhong Chen, Naichen Shi, Xubo Yue
Causal discovery is a data-driven paradigm for analyzing complex systems, while physics-based models, such as ordinary differential equations (ODEs), provide mechanistic structure…
DiffATS: Diffusion in Aligned Tensor Space
Jinhua Lyu, Tianmin Yu, Brian Kim +3
Direct diffusion modeling of high-resolution spatiotemporal fields is computationally challenging. Parameter-efficient primitives address this by representing high-dimensional data…
Domain Generalization Under Posterior Drift
Yilun Zhu, Naihao Deng, Naichen Shi +2
Domain generalization (DG) is the problem of generalizing from several distributions (or domains), for which labeled training data are available, to a new test domain for which no…