US Patent Issued to ATOMBEAM TECHNOLOGIES on Feb. 18 for "Upsampling of compressed financial time-series data using a jointly trained Vector Quantized Variational Autoencoder neural network" (Missouri, Kansas, Washington Inventors)

ALEXANDRIA, Va., Feb. 19 -- United States Patent no. 12,229,679, issued on Feb. 18, was assigned to ATOMBEAM TECHNOLOGIES INC (Moraga, Calif.).

"Upsampling of compressed financial time-series data using a jointly trained Vector Quantized Variational Autoencoder neural network" was invented by Zhu Li (Overland Park, Kan.), Brian Galvin (Silverdale, Wash.) and Paras Maharjan (Kansas City, Mo.).

According to the abstract* released by the U.S. Patent & Trademark Office: "A system and methods for upsampling compressed data using a jointly trained Vector Quantized Variational Autoencoder (VQ-VAE) and neural upsampler. The system compresses input data into a discrete latent space using a VQ-VAE encoder, reconstructs the data using a VQ-VAE decod...