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.

公开(公告)号：US20210034973A1

公开(公告)日：2021-02-04

申请号：US16943957

申请日：2020-07-30

Applicant: Google LLC

Inventor： Zhen Xu ,  Andrew M. Dai ,  Jonas Beachey Kemp ,  Luke Shekerjian Metz

IPC: G06N3/08 ,  G06N3/04

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network. One of the methods includes training the neural network for one or more training steps in accordance with a current learning rate; generating a training dynamics observation characterizing the training of the trainee neural network on the one or more training steps; providing the training dynamics observation as input to a controller neural network that is configured to process the training dynamics observation to generate a controller output that defines an updated learning rate; obtaining as output from the controller neural network the controller output that defines the updated learning rate; and setting the learning rate to the updated learning rate.

公开(公告)号：US20250118401A1

公开(公告)日：2025-04-10

申请号：US17143083

申请日：2021-01-06

Applicant: Google LLC

Inventor： Edward Choi ,  Andrew M. Dai ,  Gerardo Flores ,  Yuan Xue ,  Michael Ward Dusenberry ,  Zhen Xu ,  Yujia Li

IPC: G16H15/00 ,  G06N3/08 ,  G16H50/20

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing data about a medical encounter using neural networks. One of the methods includes obtaining features for a medical encounter associated with the patient, each feature representing a corresponding health event associated with the medical encounter and each of the plurality of features belonging to a vocabulary of possible features that each represent a different health event; and generating respective final embeddings for each of the features for the medical encounter by applying a sequence of one or more self-attention blocks to the features for the medical encounter, wherein each of the one or more self-attention blocks receives a respective block input for each of the features and applies self-attention over the block inputs to generate a respective block output for each of the features.

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：US20230274151A1

公开(公告)日：2023-08-31

申请号：US17915796

申请日：2021-03-30

Applicant: Google LLC

Inventor： Zhen Xu ,  David Richard So ,  Andrew M. Dai

IPC: G06N3/086 ,  G06N3/045

CPC classification number: G06N3/086 ,  G06N3/045

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for searching for an architecture for a neural network that performs a multi-modal task that requires operating on inputs that each include data from multiple different modalities.