Physics-Informed Machine Learning
Abstract
Data-driven discovery is revolutionizing how we model, predict, and control complex systems. Now with Python and MATLAB®, this textbook trains mathematical scientists and engineers for the next generation of scientific discovery by offering a broad overview of the growing intersection of data-driven methods, machine learning, applied optimization, and classical fields of engineering mathematics and mathematical physics. With a focus on integrating dynamical systems modeling and control with modern methods in applied machine learning, this text includes methods that were chosen for their relevance, simplicity, and generality. Topics range from introductory to research-level material, making it accessible to…
Citation impact
- FWCI
- 89.34
- Percentile
- 100%
- References
- 0
Authors
2- SLSteven L. BruntonCorresponding
University of Washington
- JNJ. Nathan Kutz
University of Washington
Topics & keywords
- Python (programming language)
- Computer science
- Generality
- MATLAB
- Artificial intelligence
- Toolbox
- Bridging (networking)
- Graduate students
- Quality Education