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Found 10 papers, 1 papers with code
Deep Learning with Passive Optical Nonlinear Mapping
Utilizing rapid optical information processing capabilities, our optical platforms could potentially offer more efficient and real-time processing solutions for a broad range of applications.
Intelligent Computing: The Latest Advances, Challenges and Future
In recent years, we have witnessed the emergence of intelligent computing, a new computing paradigm that is reshaping traditional computing and promoting digital revolution in the era of big data, artificial intelligence and internet-of-things with new computing theories, architectures, methods, systems, and applications.
Deeply Sub-Wavelength Localization with Reverberation-Coded-Aperture
We demonstrate our finding in the microwave domain: harnessing the configurational DoF of a simple programmable metasurface, we localize a sub-wavelength object inside a chaotic cavity with a resolution of $\lambda/76$ using intensity-only single-frequency single-pixel measurements.
Applied Physics Signal Processing
Hardware Beyond Backpropagation: a Photonic Co-Processor for Direct Feedback Alignment
We present a photonic accelerator for Direct Feedback Alignment, able to compute random projections with trillions of parameters.
Directional control of weakly localized Raman from a random network of fractal nanowires
By visualizing Rayleigh scattering, photoluminescence and weakly localized Raman light from the random network of nanowires via real-space microscopy and Fourier imaging, we gain insight on the light transport mechanisms responsible for the material's inelastic coherent signal and for its directionality.
Optics Disordered Systems and Neural Networks Materials Science
Light-in-the-loop: using a photonics co-processor for scalable training of neural networks
As neural networks grow larger and more complex and data-hungry, training costs are skyrocketing.
Spectral Method for Multiplexed Phase Retrieval and Application in Optical Imaging in Complex Media
We introduce a generalized version of phase retrieval called multiplexed phase retrieval.
Scaling up Echo-State Networks with multiple light scattering
As a proof of concept, binary networks have been successfully trained to predict the chaotic Mackey-Glass time series.
Random Projections through multiple optical scattering: Approximating kernels at the speed of light
Random projections have proven extremely useful in many signal processing and machine learning applications.
Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach
In this paper, the problem of compressive imaging is addressed using natural randomization by means of a multiply scattering medium.
