where \(\mathsf{G}(\cdot)\) is some convex operator and \(\mathcal{F}\) is as set of feasible input distributions. Examples of such an optimization problem include finding capacity in information ...
New review in iOptics demonstrates how AI is overcoming key challenges in metasurface design, enabling advanced applications in compact optics and computational imaging.
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
Artificial intelligence speeds metasurface design from unit cells to full optical systems, enabling compact imaging, AR and VR displays and advanced LiDAR.
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