公开(公告)号：US20240303464A1

公开(公告)日：2024-09-12

申请号：US18598876

申请日：2024-03-07

Applicant: Google LLC

Inventor： Nan Du ,  Tao Wang ,  Yanqi Zhou ,  Tao Lei ,  Yuanzhong Xu ,  Andrew Mingbo Dai ,  Zhifeng Chen ,  Dewen Zeng ,  Yingwei Cui

IPC: G06N3/04 ,  G06N3/084

CPC classification number: G06N3/04 ,  G06N3/084

Abstract: A method includes providing a first set of data objects to a first skip router of a neural network (NN). The NN includes a first NN layer and a second NN layer. The first set of data objects is subdivided into a first set of skip objects and a first set of non-skip objects based on a first skip logic implemented by the first skip router and a first context of each data object in the first set of data objects. A first set of processed objects is generated based on the first set of non-skip objects and a first layer logic implemented by the first NN layer. Predictions are generated based on a second set of data objects and a second layer logic implemented by the second NN layer. The second set of data objects includes the first set of processed objects and the first set of skip objects.

公开(公告)号：US12217144B2

公开(公告)日：2025-02-04

申请号：US17008338

申请日：2020-08-31

Applicant: Google LLC

Inventor： Yuan Xue ,  Dengyong Zhou ,  Nan Du ,  Andrew Mingbo Dai ,  Zhen Xu ,  Kun Zhang ,  Yingwei Cui

IPC: G06N20/20 ,  G06F17/16 ,  G06F17/18 ,  G06N3/02

Abstract: A deep state space generative model is augmented with intervention prediction. The state space model provides a principled way to capture the interactions among observations, interventions, critical event occurrences, true states, and associated uncertainty. The state space model can include a discrete-time hazard rate model that provides flexible fitting of general survival time distributions. The state space model can output a joint prediction of event risk, observation and intervention trajectories based on patterns in temporal progressions, and correlations between past measurements and interventions.

公开(公告)号：US20210065066A1

公开(公告)日：2021-03-04

申请号：US17008338

申请日：2020-08-31

Applicant: Google LLC

Inventor： Yuan Xue ,  Dengyong Zhou ,  Nan Du ,  Andrew Mingbo Dai ,  Zhen Xu ,  Kun Zhang ,  Yingwei Cui

IPC: G06N20/20 ,  G06N3/02 ,  G06F17/18 ,  G06F17/16

Abstract: A deep state space generative model is augmented with intervention prediction. The state space model provides a principled way to capture the interactions among observations, interventions, critical event occurrences, true states, and associated uncertainty. The state space model can include a discrete-time hazard rate model that provides flexible fitting of general survival time distributions. The state space model can output a joint prediction of event risk, observation and intervention trajectories based on patterns in temporal progressions, and correlations between past measurements and interventions.