Abstract: Embodiments are disclosed for expanding a seed scene using proposals from a generative model of scene graphs. The method may include clustering subgraphs according to respective one or more maximal connected subgraphs of a scene graph. The scene graph includes a plurality of nodes and edges. The method also includes generating a scene sequence for the scene graph based on the clustered subgraphs. A first machine learning model determines a predicted node in response to receiving the scene sequence. A second machine learning model determines a predicted edge in response to receiving the scene sequence and the predicted node. A scene graph is output according to the predicted node and the predicted edge.

Abstract: Techniques and apparatus for managing remote attestation of infrastructure components based on a customer controlled dynamic attestation policy are described. One technique includes receiving a user-specified configuration for managing remote attestation of infrastructure component(s) hosted in a cloud computing environment. The user-specified configuration indicates information related to managing the life-cycle of the infrastructure component(s). For example, the user-specified configuration can indicate attributes associated with the infrastructure component(s), criteria for validating an attestation policy for the infrastructure component(s), criteria for rotating an attestation policy for the infrastructure component(s), etc. An attestation policy for each infrastructure component is generated, based on the user-specified configuration. The attestation policy for each infrastructure component indicates which of the attributes to use during remote attestation of the infrastructure component.

Abstract: A workflow service implements policies to leverage affinities to improve system performance. Example types of policies include a parent activity affinity (e.g., data for a task already exists locally to a node), a resource group affinity (e.g., a task requires a particular type of resource capability), or a code affinity (e.g., necessary code for the task is already stored locally to a node). A node for a particular task is selected based on an affinity policy or policy statement (e.g., the type indicated in a policy of a workflow definition) and configuration information, and the task routed to the selected node.