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Found 3 papers, 1 papers with code
Backpropagation-free Training of Deep Physical Neural Networks
Recent years have witnessed the outstanding success of deep learning in various fields such as vision and natural language processing.
Variational framework for partially-measured physical system control: examples of vision neuroscience and optical random media
To characterize a physical system to behave as desired, either its underlying governing rules must be known a priori or the system itself be accurately measured.
Competing Neural Networks for Robust Control of Nonlinear Systems
The output of physical systems is often accessible by measurements such as the 3D position of a robotic arm actuated by many actuators or the speckle patterns formed by shining the spot of a laser pointer on a wall.
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