Abstract: Disclosed herein are methods and systems for implementing a multi-model computer architecture for entity identification. A method includes receiving data regarding a plurality of entities. The method includes generating a plurality of entity profiles for the plurality entities and a network graph data structure (e.g., a node graph) comprising edges between nodes for the plurality of entity profiles. The method includes executing a model using identifiers of the plurality of entity profiles, an event topic, and the edges between the nodes as input to generate one or more composite scores for the plurality of entity profiles. The method includes selecting one or more entities for the event based on the generated one or more composite scores. The method includes generating a record comprising associations between identifications of the entities and the event.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for object recognition neural network for amodal center prediction. One of the methods includes receiving an image of an object captured by a camera. The image of the object is processed using an object recognition neural network that is configured to generate an object recognition output. The object recognition output includes data defining a predicted two-dimensional amodal center of the object, wherein the predicted two-dimensional amodal center of the object is a projection of a predicted three-dimensional center of the object under a camera pose of the camera that captured the image.

Abstract: Disclosed are methods, apparatus, systems, and computer readable storage media for publishing a marketing campaign on an online social network. A CRM server accesses a marketing campaign record in a database and transmits marketing campaign data to be published on an online social network. The CRM server also receives data related to users interacting with the published marketing campaign. The CRM server can store the user-related data. In some implementations, the user-related data can also be analyzed.