US 12,481,865 B2
Quantum deformed binary neural networks
Roberto Bondesan, Amsterdam (NL); and Max Welling, Bussum (NL)
Assigned to Qualcomm Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on Sep. 30, 2021, as Appl. No. 17/491,426.
Claims priority of provisional application 63/086,463, filed on Oct. 1, 2020.
Prior Publication US 2022/0108154 A1, Apr. 7, 2022
Int. Cl. G06N 3/047 (2023.01); G06F 18/21 (2023.01); G06N 3/08 (2023.01); G06N 10/00 (2022.01); G06V 10/94 (2022.01)
CPC G06N 3/047 (2023.01) [G06F 18/217 (2023.01); G06N 3/08 (2013.01); G06N 10/00 (2019.01); G06V 10/95 (2022.01)] 16 Claims
OG exemplary drawing
 
1. A method for processing data in a quantum deformed binary neural network, comprising:
determining an input state for a layer of the quantum deformed binary neural network based on input image data, wherein the quantum deformed binary neural network is configured to perform the determining of the input state based on the input image data and a quantum phase estimation;
computing statistics for one or more observables in the layer, wherein the quantum deformed binary neural network is configured to perform the computing of the statistics based on using a quantum circuit with one or more entangled qubits comprising activation bits and weight bits that are entangled with one another to process the input state;
returning, by the quantum deformed binary neural network, an output activation probability based on the statistics for the one or more observables in the layer; and
assigning a classification to the input image data based on the output activation probability.