X Development LLC

Lance Co Ting Keh

Artem Goncharuk

Allen Richard Zhao

Hongxu Ma

Jie Jacquot

Vadim Tschernezki

Gearoid Murphy

Diosdado Rey Banatao

Sujit Sanjeev

Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, for machine learning classification based on separate processing of multiple views. In some implementations, a system obtains image data for multiple images showing different views of an object. A machine learning model is used to generate a separate output based on each the multiple images individually. The outputs for the respective images are combined to generate a combined output. A predicted characteristic of the object is determined based on the combined output. An indication of the predicted characteristic of the object is provided.

Machine learning classification based on separate processing of multiple views

The present disclosure relates to techniques for deformulating the spectra of arbitrary compound formulations such as polymer formulations into their chemical components. Particularly, aspects of the present disclosure are directed to obtaining an initial set of spectra for a plurality of samples comprising pure samples and composite samples, constructing a basis set of spectra for a plurality of pure samples based on the initial set of spectra, and providing or outputting the basis set of spectrum. The basis set of spectra is constructed in an iterative process that attempts to decompose, using a decomposition algorithm or model, the spectrum from the initial set of spectra in order to differentiate the pure samples from the composite samples. The basis set of spectra may then be used to deduce the composition of a material from a spectrogram.

Deformulation techniques for deducing the composition of a material from a spectrogram

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La Crescenta, CA, United States of America

Lance Co Ting Keh