Michael Mahoney - Dynamical systems and machine learning
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Jeff Moehlis - Learning How to Control Populations of Neurons
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Zico Kolter - Incorporating physics and decision making into deep learning via implicit layers
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Deep Learning to Discover Coordinates for Dynamics: Autoencoders & Physics Informed Machine Learning
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Data-driven model discovery: Targeted use of deep neural networks for physics and engineering
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MIT Introduction to Deep Learning | 6.S191
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DeepOnet: Learning nonlinear operators based on the universal approximation theorem of operators.
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NeurIPS 2020 Tutorial: Deep Implicit Layers
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