Learning operators using deep neural networks for multiphysics, multiscale, & multifidelity problems
1:48:20
New architectures for DeepONet || Ehnacing ML with Physics || Seminar on October 20, 2023
58:12
DeepOnet: Learning nonlinear operators based on the universal approximation theorem of operators.
1:07:58
MIT 6.S191: Convolutional Neural Networks
59:40
DDPS | Deep neural operators with reliable extrapolation for multiphysics & multiscale problems
45:59
EI 2023 Plenary 1: Neural Operators for Solving PDEs
26:12
ECCE2024 Presentation (Battery Temperature Prediction)
36:30
AI/ML+Physics Part 3: Designing an Architecture [Physics Informed Machine Learning]
59:00