Patents by Inventor Jonathon Shlens
Jonathon Shlens has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 11960519Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for classifying data objects. One of the methods includes obtaining data that associates each term in a vocabulary of terms with a respective high-dimensional representation of the term; obtaining classification data for a data object, wherein the classification data includes a respective score for each of a plurality of categories, and wherein each of the categories is associated with a respective category label; computing an aggregate high-dimensional representation for the data object from high-dimensional representations for the category labels associated with the categories and the respective scores; identifying a first term in the vocabulary of terms having a high-dimensional representation that is closest to the aggregate high-dimensional representation; and selecting the first term as a category label for the data object.Type: GrantFiled: August 20, 2020Date of Patent: April 16, 2024Assignee: Google LLCInventors: Gregory Sean Corrado, Tomas Mikolov, Samy Bengio, Yoram Singer, Jonathon Shlens, Andrea L Frome, Jeffrey Adgate Dean, Mohammad Norouzi
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Publication number: 20230410389Abstract: A method for applying a style to an input image to generate a stylized image. The method includes maintaining data specifying respective parameter values for each image style in a set of image styles, receiving an input including an input image and data identifying an input style to be applied to the input image to generate a stylized image that is in the input style, determining, from the maintained data, parameter values for the input style, and generating the stylized image by processing the input image using a style transfer neural network that is configured to process the input image to generate the stylized image.Type: ApplicationFiled: September 6, 2023Publication date: December 21, 2023Inventors: Jonathon Shlens, Vincent Dumoulin, Manjunath Kudlur Venkatakrishna
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Patent number: 11847541Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model. One of the methods includes obtaining a training data set for training a machine learning model, the training data set comprising a plurality of training inputs; determining a plurality of data augmentation policies, wherein each data augmentation policy defines a procedure for processing a training input to generate a transformed training input; for each data augmentation policy, training the machine learning model using the data augmentation policy; determining, for each data augmentation policy, a quality measure of the machine learning model that has been trained using the data augmentation policy; and selecting a final data augmentation policy based using the quality measures of the machine learning models.Type: GrantFiled: December 20, 2021Date of Patent: December 19, 2023Assignee: Google LLCInventors: Jonathon Shlens, Quoc V. Le, Ekin Dogus Cubuk, Barret Zoph
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Patent number: 11790233Abstract: The specification describes methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a larger neural network from a smaller neural network. One of the described methods includes obtaining data specifying an original neural network and generating a larger neural network from the original neural network. The larger neural network has a larger neural network structure than the original neural network structure. The values of the parameters of the original neural network units and the additional neural network units are initialized so that the larger neural network generates the same outputs from the same inputs as the original neural network, and the larger neural network is trained to determine trained values of the parameters of the original neural network units and the additional neural network units from the initialized values.Type: GrantFiled: June 29, 2020Date of Patent: October 17, 2023Assignee: Google LLCInventors: Ian Goodfellow, Tianqi Chen, Jonathon Shlens
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Patent number: 11774596Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing data generated by a sensing system that rotationally senses an environment. In one aspect, a method comprises partitioning a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by the sensing system constitutes a complete rotational sensing of the environment; for each sub-period: receiving current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment; processing the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment.Type: GrantFiled: September 1, 2022Date of Patent: October 3, 2023Assignee: Google LLCInventors: Jonathon Shlens, Vijay Vasudevan, Jiquan Ngiam, Wei Han, Zhifeng Chen, Brandon Chauloon Yang, Benjamin James Caine, Zhengdong Zhang, Christoph Sprunk, Ouais Alsharif, Junhua Mao, Chen Wu
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Patent number: 11776167Abstract: A method for applying a style to an input image to generate a stylized image. The method includes maintaining data specifying respective parameter values for each image style in a set of image styles, receiving an input including an input image and data identifying an input style to be applied to the input image to generate a stylized image that is in the input style, determining, from the maintained data, parameter values for the input style, and generating the stylized image by processing the input image using a style transfer neural network that is configured to process the input image to generate the stylized image.Type: GrantFiled: November 12, 2019Date of Patent: October 3, 2023Assignee: Google LLCInventors: Jonathon Shlens, Vincent Dumoulin, Manjunath Kudlur Venkatakrishna
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Publication number: 20230252327Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes generating, using a controller neural network having controller parameters and in accordance with current values of the controller parameters, a batch of output sequences. The method includes, for each output sequence in the batch: generating an instance of a child convolutional neural network (CNN) that includes multiple instances of a first convolutional cell having an architecture defined by the output sequence; training the instance of the child CNN to perform an image processing task; and evaluating a performance of the trained instance of the child CNN on the task to determine a performance metric for the trained instance of the child CNN; and using the performance metrics for the trained instances of the child CNN to adjust current values of the controller parameters of the controller neural network.Type: ApplicationFiled: April 20, 2023Publication date: August 10, 2023Inventors: Vijay Vasudevan, Barret Zoph, Jonathon Shlens, Quoc V. Le
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Patent number: 11651259Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining neural network architectures. One of the methods includes generating, using a controller neural network having controller parameters and in accordance with current values of the controller parameters, a batch of output sequences. The method includes, for each output sequence in the batch: generating an instance of a child convolutional neural network (CNN) that includes multiple instances of a first convolutional cell having an architecture defined by the output sequence; training the instance of the child CNN to perform an image processing task; and evaluating a performance of the trained instance of the child CNN on the task to determine a performance metric for the trained instance of the child CNN; and using the performance metrics for the trained instances of the child CNN to adjust current values of the controller parameters of the controller neural network.Type: GrantFiled: November 5, 2019Date of Patent: May 16, 2023Assignee: Google LLCInventors: Vijay Vasudevan, Barret Zoph, Jonathon Shlens, Quoc V. Le
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Patent number: 11544869Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating object interaction predictions using a neural network. One of the methods includes obtaining a sensor input derived from data generated by one or more sensors that characterizes a scene. The sensor input is provided to an object interaction neural network. The object interaction neural network is configured to process the sensor input to generate a plurality of object interaction outputs. Each respective object interaction output includes main object information and interacting object information. The respective object interaction outputs corresponding to the plurality of regions in the sensor input are received as output of the object interaction neural network.Type: GrantFiled: June 8, 2021Date of Patent: January 3, 2023Assignee: Waymo LLCInventors: Alper Ayvaci, Yu-Han Chen, Ruichi Yu, Chen Wu, Noha Waheed Ahmed Radwan, Jonathon Shlens
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Publication number: 20220415042Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing data generated by a sensing system that rotationally senses an environment. In one aspect, a method comprises partitioning a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by the sensing system constitutes a complete rotational sensing of the environment; for each sub-period: receiving current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment; processing the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment.Type: ApplicationFiled: September 1, 2022Publication date: December 29, 2022Inventors: Jonathon Shlens, Vijay Vasudevan, Jiquan Ngiam, Wei Han, Zhifeng Chen, Brandon Chauloon Yang, Benjamin James Caine, Zhengdong Zhang, Christoph Sprunk, Ouais Alsharif, Junhua Mao, Chen Wu
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Publication number: 20220383076Abstract: A method for performing one or more tasks, wherein each of the one or more tasks includes predicting behavior of one or more agents in an environment, the method comprising: obtaining a three-dimensional (3D) input tensor representing behaviors of the one or more agents in the environment across a plurality of time steps; generating an encoded representation of the 3D input tensor by processing the 3D input tensor using an encoder neural network, wherein 3D input tensor comprises a plurality of observed cells and a plurality of masked cells; and processing the encoded representation of the 3D input tensor using a decoder neural network to generate a 4D output tensor.Type: ApplicationFiled: May 31, 2022Publication date: December 1, 2022Inventors: Jonathon Shlens, Vijay Vasudevan, Jiquan Ngiam, Benjamin James Caine, Zhengdong Zhang, Zhifeng Chen, Hao-Tien Chiang, David Joseph Weiss, Jeffrey Ling, Ashish Venugopal
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Patent number: 11508147Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing data generated by a sensing system that rotationally senses an environment. In one aspect, a method comprises partitioning a predetermined period of time into a plurality of sub-periods, wherein the predetermined period of time is a period of time for which data generated by the sensing system constitutes a complete rotational sensing of the environment; for each sub-period: receiving current data generated by the sensing system during the sub-period and characterizing a respective partial scene of the environment; processing the current data using an object detection neural network to generate a current object detection output that is specific to the respective partial scene of the environment.Type: GrantFiled: March 6, 2020Date of Patent: November 22, 2022Assignee: Google LLCInventors: Jonathon Shlens, Vijay Vasudevan, Jiquan Ngiam, Wei Han, Zhifeng Chen, Brandon Chauloon Yang, Benjamin James Caine, Zhengdong Zhang, Christoph Sprunk, Ouais Alsharif, Junhua Mao, Chen Wu
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Publication number: 20220319054Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting scene flow. One of the methods includes obtaining a current point cloud representing an observed scene at a current time point; obtaining object label data that identifies a first three-dimensional region in the observed scene; determining, for each current three-dimensional point that is within the first three-dimensional region and using the object label data, a respective preceding position of the current three-dimensional point at a preceding time point in a reference frame of the sensor at the current time point; and generating, using the preceding positions, a scene flow label for the current point cloud that comprises a respective ground truth motion vector for each of a plurality of the current three-dimensional points.Type: ApplicationFiled: March 1, 2022Publication date: October 6, 2022Inventors: Nichola Abdo, Jonathon Shlens, Zhifeng Chen, Christopher John Sweeney, Philipp Florian Jund
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Patent number: 11450120Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing point cloud data representing a sensor measurement of a scene captured by one or more sensors to generate an object detection output that identifies locations of one or more objects in the scene. When deployed within an on-board system of a vehicle, the object detection output that is generated can be used to make autonomous driving decisions for the vehicle with enhanced accuracy.Type: GrantFiled: July 8, 2020Date of Patent: September 20, 2022Assignee: Waymo LLCInventors: Jonathon Shlens, Patrick An Phu Nguyen, Benjamin James Caine, Jiquan Ngiam, Wei Han, Brandon Chauloon Yang, Yuning Chai, Pei Sun, Yin Zhou, Xi Yi, Ouais Alsharif, Zhifeng Chen, Vijay Vasudevan
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Publication number: 20220215654Abstract: A system implemented as computer programs on one or more computers in one or more locations that implements a computer vision model is described. The computer vision model includes a positional local self-attention layer that is configured to receive an input feature map and to generate an output feature map. For each input element in the input feature map, the positional local self-attention layer generates a respective output element for the output feature map by generating a memory block including neighboring input elements around the input element, generates a query vector using the input element and a query weight matrix, for each neighboring element in the memory block, performs positional local self-attention operations to generate a temporary output element, and generates the respective output element by summing temporary output elements of the neighboring elements in the memory block.Type: ApplicationFiled: May 22, 2020Publication date: July 7, 2022Inventors: Jonathon Shlens, Ashish Teku Vaswani, Niki J. Parmar, Prajit Ramachandran, Anselm Caelifer Levskaya, Irwan Bello
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Publication number: 20220180193Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a neural network to perform 3D object detection. One of the methods includes training a student neural network to perform 3D object detection using pseudo-labels generated by a teacher neural network.Type: ApplicationFiled: December 9, 2021Publication date: June 9, 2022Inventors: Benjamin James Caine, Rebecca Dawn Roelofs, Jonathon Shlens, Zhifeng Chen, Jiquan Ngiam, Vijay Vasudevan
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Publication number: 20220114400Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model. One of the methods includes obtaining a training data set for training a machine learning model, the training data set comprising a plurality of training inputs; determining a plurality of data augmentation policies, wherein each data augmentation policy defines a procedure for processing a training input to generate a transformed training input; for each data augmentation policy, training the machine learning model using the data augmentation policy; determining, for each data augmentation policy, a quality measure of the machine learning model that has been trained using the data augmentation policy; and selecting a final data augmentation policy based using the quality measures of the machine learning models.Type: ApplicationFiled: December 20, 2021Publication date: April 14, 2022Inventors: Jonathon Shlens, Quoc V. Le, Ekin Dogus Cubuk, Barret Zoph
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Patent number: 11257217Abstract: A method for generating a segmentation of an image that assigns each pixel to a respective segmentation category from a set of segmentation categories is described. The method includes obtaining features of the image, the image including a plurality of pixels. For each of one or more time steps starting from an initial time step and continuing until a final time step, the method includes generating a network input from the features of the image and a current segmentation output as of the time step, processing the network input using a convolutional recurrent neural network to generate an intermediate segmentation output for the time step, and generating an updated segmentation output for the time step from the intermediate segmentation output for the time step and the current segmentation output as of the time step. The method includes generating a final segmentation of the image from the updated segmentation output.Type: GrantFiled: November 20, 2018Date of Patent: February 22, 2022Assignee: Google LLCInventors: Jonathon Shlens, Niruban Maheswaranathan, David Sussillo
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Patent number: 11205099Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training a machine learning model. One of the methods includes obtaining a training data set for training a machine learning model, the training data set comprising a plurality of training inputs; determining a plurality of data augmentation policies, wherein each data augmentation policy defines a procedure for processing a training input to generate a transformed training input; for each data augmentation policy, training the machine learning model using the data augmentation policy; determining, for each data augmentation policy, a quality measure of the machine learning model that has been trained using the data augmentation policy; and selecting a final data augmentation policy based using the quality measures of the machine learning models.Type: GrantFiled: March 27, 2020Date of Patent: December 21, 2021Assignee: Google LLCInventors: Jonathon Shlens, Quoc V. Le, Ekin Dogus Cubuk, Barret Zoph
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Publication number: 20210334624Abstract: A method for determining an architecture for a task neural network configured to perform a particular machine learning task is described.Type: ApplicationFiled: July 1, 2021Publication date: October 28, 2021Inventors: Wei Hua, Barret Zoph, Jonathon Shlens, Chenxi Liu, Jonathan Huang, Jia Li, Fei-Fei Li, Kevin Patrick Murphy