S19-323 Simultaneous Measurements of Gradients in Optical Networks Stanford researchers have an efficient method to measure gradients simultaneously and in parallel, as related to an optical network. Shanhui Fan Tyler Hughes David Miller Sunil Pai Olav Solgaard Ian Williamson
S18-093B Systems and Methods for Activation Functions for Photonic Neural Networks Stanford researchers have developed an electro-optic hardware platform for nonlinear activation functions in optical neural networks. Shanhui Fan Tyler Hughes Momchil Minkov Ian Williamson
S18-093 Efficient, Scalable Training of Artificial Neural Networks Directly on Optical Devices Engineers in Prof. Shanhui Fan's laboratory have developed an efficient, scalable, in-situ method to train, configure and tune complex photonic circuits for artificial intelligence and machine learning. Tyler Hughes Momchil Minkov Shanhui Fan Ian Williamson