Snap Inc.

Yanping Chen

Jaewook Chung

Wisam Dakka

Emre Yamangil

Theresa Barton

Xin Chen

Jiwoon Jeon

Lucas Ou-Yang

Keyang Zhang

Sergey Tulyakov

Sergei Kotcur

Igor Kudriashov

Christopher Yale Crutchfield

Aymeric Damien

Andrew Wan

Disclosed are methods and systems for ranking content. In one aspect, a method of ranking content for display includes identifying, via hardware processing circuitry, interactions by a single account with content pairs, each of the content in the content pairs included in a plurality of content, aggregating, via the hardware processing circuitry, the identified interactions across a plurality of accounts, associating, via the hardware processing circuitry, probabilities with each content in the plurality of content based on the aggregated interactions, ranking, via the hardware processing circuitry, the plurality of content based on the associated probabilities; and selecting, via the hardware processing circuitry, content ranked above a threshold for display.

Ranking content for display

A system of machine learning schemes can be configured to efficiently perform image processing tasks on a user device, such as a mobile phone. The system can selectively detect and transform individual regions within each frame of a live streaming video. The system can selectively partition and toggle image effects within the live streaming video.

Device-based image modification of depicted objects

A multistage neural network system can store neural networks as shader programs on GPU memory. Neural network weights can be stored as shader objects or textures on the GPU memory. The GPU can receive a number of neural network image processing tasks to perform on images captured by a client device. The GPU can execute the tasks per driver parameters and display results in real time or near real time on the client device.

Multistage neural network processing using a graphics processor

Growing community of inventors

San Jose, CA, United States of America

Yanping Chen