Physics-Informed Machine Learning: Using the Laws of Nature to Improve Generalized Deep Learning Models
23:59
mathworks.com
Physics-Informed Machine Learning: Using the Laws of Nature to Improve Generalized Deep Learning Models
Conventional deep learning uses loss functions based on the data to ensure that the best model can be found. However, when dealing with physical systems we must include the laws of physics into these functions. Here we show how this can be achieved.
May 26, 2021
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QuantMaxxing on Instagram: "Terence Tao is one of the most accomplished mathematicians of the modern era, known for extraordinary breadth and depth across many fields. Often called the “Mozart of mathematics,” he became a professor at UCLA at a very young age and won the Fields Medal (2006) for major contributions to analysis, number theory, and partial differential equations. His work spans areas such as harmonic analysis, analytic number theory, PDEs, additive combinatorics, random matrix theo
0:17
QuantMaxxing on Instagram: "Terence Tao is one of the most accomplished mathematicians of the modern era, known for extraordinary breadth and depth across many fields. Often called the “Mozart of mathematics,” he became a professor at UCLA at a very young age and won the Fields Medal (2006) for major contributions to analysis, number theory, and partial differential equations. His work spans areas such as harmonic analysis, analytic number theory, PDEs, additive combinatorics, random matrix theo
Instagramquantmaxxing
3.2M views3 months ago
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