Results 261 to 270 of about 11,198,121 (288)

Probabilistic Physics-Informed Machine Learning for Dynamic Systems

Reliability Engineering and System Safety, 2023
Sankaran Mahadevan, Abhinav Subramanian
exaly   +3 more sources

Physics-Informed Machine Learning for Battery Degradation Diagnostics: A Comparison of State-of-the-Art Methods [PDF]

Energy Storage Materials
Monitoring the health of lithium-ion batteries' internal components as they age is crucial for optimizing cell design and usage control strategies. However, quantifying component-level degradation typically involves aging many cells and destructively ...
Chao Hu, Tingkai Li
exaly   +2 more sources

Physics-Informed Machine Learning in Geotechnical Engineering: A Direction Paper [PDF]

Geomechanics and Geoengineering
This direction paper explores the evolving landscape of physics-informed machine learning (PIML) methodologies in the field of geotechnical engineering, aiming to provide a comprehensive overview of current advancements and propose future research ...
Xiaohui Chen, Jinhyun Choo, Yanjie Song
exaly   +3 more sources

Physics-informed Machine Learning for Medical Image Analysis

ACM Computing Surveys
The incorporation of physical information in machine learning frameworks is transforming medical image analysis (MIA). Integrating fundamental knowledge and governing physical laws not only improves analysis performance but also enhances the model’s robustness and interpretability.
Chayan Banerjee, Kien Nguyen 0001, Olivier Salvado, Truyen Tran 0001, Clinton Fookes   +4 more
openaire   +2 more sources

Separable physics-informed DeepONet: Breaking the curse of dimensionality in physics-informed machine learning

Computer Methods in Applied Mechanics and Engineering
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luis Mandl, Somdatta Goswami, Lena Lambers, Tim Ricken   +3 more
openaire   +1 more source

From Physics-Informed Machine Learning to Physics-Informed Machine Intelligence: Quo Vadimus?

This talk reviews physics-informed neural networks and introduces networks that learn functionals and nonlinear operators for system identification. It discusses applications in digital twins, autonomy, and materials discovery, and introduces bio-inspired solutions like spiking neural networks and neuromorphic computing.
openaire   +1 more source

Physics-Informed Machine Learning

2022
openaire   +1 more source

Machine Learning in Epigenetic Diseases

Medical Epigenetics, 2021
Robert E Akins, Karyn Robinson
exaly  

Physics-Informed Machine Learning for Reliability and Systems Safety Applications: State of the Art and Challenges

Reliability Engineering and System Safety, 2023
Pingfeng Wang, Jessica Boakye, Yanwen Xu
exaly  

On the Feasibility of Using Physics-Informed Machine Learning for Underground Reservoir Pressure Management

Expert Systems With Applications, 2021
Bicheng Yan, Daniel O'Malley, Rajesh Pawar   +2 more
exaly