3 papers
cs.LG2026
Physics-informed Diffusion Generative Model for Time-Series Data Synthesis in Dynamic Systems
Haiteng Wang, Yunfei Zhu, Tao Wang +4
Industrial time-series signals, such as turbine temperature and rotational speed in aero-engines, are essential for monitoring the health and operational status of complex dynamica…
cs.SE2026
A Hierarchical Imprecise Probability Approach to Reliability Assessment of Large Language Models
Robab Aghazadeh-Chakherlou, Qing Guo, Siddartha Khastgir +3
Large Language Models (LLMs) are increasingly deployed across diverse domains, raising the need for rigorous reliability assessment methods. Existing benchmark-based evaluations pr…
cs.LG2024
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge
Xiaoge Zhang, Xiao-Lin Wang, Fenglei Fan +2
In this paper, we develop a generic methodology to encode hierarchical causality structure among observed variables into a neural network in order to improve its predictive perform…