62 citations · 66 across the 4 of their papers we have counts for
4 papers
Application of probabilistic modeling and automated machine learning framework for high-dimensional stress field
Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi +6
Modern computational methods, involving highly sophisticated mathematical formulations, enable several tasks like modeling complex physical phenomenon, predicting key properties an…
Distilling Governing Laws and Source Input for Dynamical Systems from Videos
Lele Luan, Yang Liu, Hao Sun
Distilling interpretable physical laws from videos has led to expanded interest in the computer vision community recently thanks to the advances in deep learning, but still remains…
Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos
Lele Luan, Yang Liu, Hao Sun
Distilling analytical models from data has the potential to advance our understanding and prediction of nonlinear dynamics. Although discovery of governing equations based on obser…
Extracting full-field subpixel structural displacements from videos via deep learning
Lele Luan, Jingwei Zheng, Yongchao Yang +2
This paper develops a deep learning framework based on convolutional neural networks (CNNs) that enable real-time extraction of full-field subpixel structural displacements from vi…