3 papers
cs.LG2026
TabPFN for Zero-shot Parametric Engineering Design Generation
Ke Wang, Yifan Tang, Nguyen Gia Hien Vu +2
Deep generative models for engineering design often require substantial computational cost, large training datasets, and extensive retraining when design requirements or datasets c…
cs.LG2026
RePaint-Enhanced Conditional Diffusion Model for Parametric Engineering Designs under Performance and Parameter Constraints
Ke Wang, Nguyen Gia Hien Vu, Yifan Tang +2
This paper presents a RePaint-enhanced framework that integrates a pre-trained performance-guided denoising diffusion probabilistic model (DDPM) for performance- and parameter-cons…
cs.CE2025
Capturing Lifecycle System Degradation in Digital Twin Model Updating
Yifan Tang, Mostafa Rahmani Dehaghani, G. Gary Wang
Digital twin (DT) has emerged as a powerful tool to facilitate monitoring, control, and other decision-making tasks in real-world engineering systems. Online update methods have be…