MarketWatch, May 4, 2021. Caspar.AI uses the whole home as a sensor – already existing elements like sensors on switches and appliances. From automated control of lights, shades and temperature to more complex tasks such as fall detection, the Caspar system works without cameras and without “wearables” such as resident pendants.
Structural-RNN: Deep Learning on Spatio-Temporal Graphs. CVPR, 2016. (oral, best student paper award)
This paper proposes a scalable and principled approach for casting an arbitrary spatio-temporal graph as a rich Recurrent Neural Network (RNN).
Such architectures are crucial for applications relating to user activities and interactions with their home environments.