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Found 4 papers, 2 papers with code
Learning to Compose SuperWeights for Neural Parameter Allocation Search
To address this, we generate layer weights by learning to compose sets of SuperWeights, which represent a group of trainable parameters.
MixtureGrowth: Growing Neural Networks by Recombining Learned Parameters
Newly grown layer weights are generated by using a new linear combination of existing templates for a layer.
A needle-based deep-neural-network camera
We experimentally demonstrate a camera whose primary optic is a cannula (diameter=0. 22mm and length=12. 5mm) that acts a lightpipe transporting light intensity from an object plane (35cm away) to its opposite end.
Classification of optics-free images with deep neural networks
The thinnest possible camera is achieved by removing all optics, leaving only the image sensor.
