Uploaded August 2024 | Updated September 2026, 1 week ago
🌎 GitHub Repository: github.com/matlab-deep-learning/physics-informed-neural-networks-with-matlab-live-coding-session
Relevant Material:
🌎 mathworks.com/help/deeplearning/ug/solve-odes-using-a-neural-network.html
🌎 mathworks.com/help/deeplearning/ug/solve-partial-differential-equations-with-lbfgs-method-and-deep-learning.html
🌎 mathworks.com/help/pde/ug/solve-poisson-equation-on-unit-disk-using-pinn.html
🌎 github.com/matlab-deep-learning/Inverse-Problems-using-Physics-Informed-Neural-Networks-PINNs
👉 Connect with Conor Daly: linkedin.com/in/conor-daly-4128b6a4
💻 A brief introduction to building and training physics-informed neural networks in MATLAB. Physics-informed neural networks (PINNs) offer a new and versatile approach for solving scientific problems by combining deep learning with known physical laws. Such networks can simulate physical systems, invert for their underlying parameters, and even discover underlying physical laws.
In this introductory workshop and live coding session, we will cover the basic definition of a PINN, its pros and cons compared to traditional scientific techniques, and some of the state-of-the-art research in the field.
Learn how to define and train physics-informed neural networks in MATLAB, including:
👉 How to define loss functions including differential equations
👉 How to combine equation losses, boundary and initial conditions and supervised losses
👉 How to write neural network training loops in MATLAB
👉 How to define neural network architectures
ONLINE PRESENCE
================
🌍 Marketing for Your Business - theapexconsulting.com
🌍 My website - jousefmurad.com
💌 My weekly science newsletter - jousef.substack.com
📸 Instagram - instagram.com/jousefmrd
🐦 X - https://x.com/jousefm2
SUPPORT MY WORK
=================
🧠 Subscribe for more free videos: bit.ly/2RLmMxq
👉 Support my Channel: https://www.jousefmurad.com/#/portal/...
CONTACT:
————————
If you need help or have any questions or want to collaborate feel free to reach out to me via email: support@jousefmurad.com
#pinns
#matlab
#coding
🌎 GitHub Repository: github.com/matlab-deep-learning/physics-informed-neural-networks-with-matlab-live-coding-session
Relevant Material:
🌎 mathworks.com/help/deeplearning/ug/solve-odes-using-a-neural-network.html
🌎 mathworks.com/help/deeplearning/ug/solve-partial-differential-equations-with-lbfgs-method-and-deep-learning.html
🌎 mathworks.com/help/pde/ug/solve-poisson-equation-on-unit-disk-using-pinn.html
🌎 github.com/matlab-deep-learning/Inverse-Problems-using-Physics-Informed-Neural-Networks-PINNs
👉 Connect with Conor Daly: linkedin.com/in/conor-daly-4128b6a4
💻 A brief introduction to building and training physics-informed neural networks in MATLAB. Physics-informed neural networks (PINNs) offer a new and versatile approach for solving scientific problems by combining deep learning with known physical laws. Such networks can simulate physical systems, invert for their underlying parameters, and even discover underlying physical laws.
In this introductory workshop and live coding session, we will cover the basic definition of a PINN, its pros and cons compared to traditional scientific techniques, and some of the state-of-the-art research in the field.
Learn how to define and train physics-informed neural networks in MATLAB, including:
👉 How to define loss functions including differential equations
👉 How to combine equation losses, boundary and initial conditions and supervised losses
👉 How to write neural network training loops in MATLAB
👉 How to define neural network architectures
ONLINE PRESENCE
================
🌍 Marketing for Your Business - theapexconsulting.com
🌍 My website - jousefmurad.com
💌 My weekly science newsletter - jousef.substack.com
📸 Instagram - instagram.com/jousefmrd
🐦 X - https://x.com/jousefm2
SUPPORT MY WORK
=================
🧠 Subscribe for more free videos: bit.ly/2RLmMxq
👉 Support my Channel: https://www.jousefmurad.com/#/portal/...
CONTACT:
————————
If you need help or have any questions or want to collaborate feel free to reach out to me via email: support@jousefmurad.com
#pinns
#matlab
#coding
