DeepOnet: Learning nonlinear operators based on the universal approximation theorem of operators.
17:46
Fourier Neural Operator (FNO) [Physics Informed Machine Learning]
7:21
The Universal Approximation Theorem of Neural Networks
59:56
Anima Anandkumar - Neural operator: A new paradigm for learning PDEs
16:20
Solving PDEs using Machine Learning by Balaji Srinivasan, IIT Madras
48:40
Representations vs Algorithms: Symbols and Geometry in Robotics
1:03:21
George Karniadakis: Approximating functions, functionals and operators with neural networks
1:11:50
Learning operators using deep neural networks for multiphysics, multiscale, & multifidelity problems
17:17