Integrating scientific knowledge with machine learning for engineering and environmental systems

J Willard, X Jia, S Xu, M Steinbach, V Kumar - ACM Computing Surveys, 2022 - dl.acm.org
There is a growing consensus that solutions to complex science and engineering problems
require novel methodologies that are able to integrate traditional physics-based modeling …

[HTML][HTML] A review of physics-based machine learning in civil engineering

SR Vadyala, SN Betgeri, JC Matthews… - Results in Engineering, 2022 - Elsevier
The recent development of machine learning (ML) and Deep Learning (DL) increases the
opportunities in all the sectors. ML is a significant tool that can be applied across many …

[PDF][PDF] Integrating physics-based modeling with machine learning: A survey

J Willard, X Jia, S Xu, M Steinbach… - ar** baseline
H Fang, HS Fang, S Xu, C Lu - IEEE Robotics and Automation …, 2022 - ieeexplore.ieee.org
Transparent objects are common in our daily life and frequently handled in the automated
production line. Robust vision-based robotic gras** and manipulation for these objects …

Incorporating physics into data-driven computer vision

A Kadambi, C de Melo, CJ Hsieh… - Nature Machine …, 2023 - nature.com
Many computer vision techniques infer properties of our physical world from images.
Although images are formed through the physics of light and mechanics, computer vision …

Shape from polarization for complex scenes in the wild

C Lei, C Qi, J **e, N Fan, V Koltun… - Proceedings of the …, 2022 - openaccess.thecvf.com
We present a new data-driven approach with physics-based priors to scene-level normal
estimation from a single polarization image. Existing shape from polarization (SfP) works …

Deep polarization imaging for 3d shape and svbrdf acquisition

V Deschaintre, Y Lin, A Ghosh - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
We present a novel method for efficient acquisition of shape and spatially varying
reflectance of 3D objects using polarization cues. Unlike previous works that have exploited …