Official implementation of Neural Lithography (SIGGRAPH Asia 2023)
Official repo for separable operator networks -- extreme-scale operator learning for parametric PDEs.
A physics-informed deep learning (DL)-based constitutive model for investigating epoxy based composites under different ambient conditions.
📕Code for paper Parallelizable Complex Neural Dynamics Models for PMSM Temperature Estimation with Hardware Acceleration.
NeedForHat Diagnosis: physics informed machine learning models for the residential energy transition
"Bayesian Enhanced AoA Estimator: A Physics-Informed Machine Learning Approach for Accurate Angle of Arrival Estimation". This repository is an AoA estimator for passive UHF RFID based on Bayesian regression and classical antenna array signal processing. Combines physics-informed analysis with Pyro-based uncertainty quantification.
Main codes for half-cell model, PINN and co-kriging implemented for physics-informed degradation diagnostics project: https://doi.org/10.1016/j.ensm.2024.103343
This is a repo for my MSc Machine Learning Final Project. Research on PINN, DRM and WAN
Physics-informed modeling of magnesium alloy dissolution in brine. Combines electrochemical theory (Butler-Volmer) with statistical learning for predicting dissolution rates in oil & gas downhole tools.
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