3 papers
cs.LG2026
A Deep Probabilistic Flow-Based Framework for Unsupervised Cross-Domain Soft Sensing
Junn Yong Loo, Hwa Hui Tew, Fang Yu Leong +4
Industrial soft sensing is crucial for accurate process monitoring through reliable inference of dominant sensor variables. However, developing effective data-driven soft sensor mo…
eess.SY2024
Sigma-point Kalman Filter with Nonlinear Unknown Input Estimation via Optimization and Data-driven Approach for Dynamic Systems
Junn Yong Loo, Ze Yang Ding, Vishnu Monn Baskaran +2
Most works on joint state and unknown input (UI) estimation require the assumption that the UIs are linear; this is potentially restrictive as it does not hold in many intelligent…
cs.RO2024
Cross-domain Transfer Learning and State Inference for Soft Robots via a Semi-supervised Sequential Variational Bayes Framework
Shageenderan Sapai, Junn Yong Loo, Ze Yang Ding +4
Recently, data-driven models such as deep neural networks have shown to be promising tools for modelling and state inference in soft robots. However, voluminous amounts of data are…