Patents Issued in February 1, 2024
  • Publication number: 20240037398
    Abstract: Some embodiments involve a reinforcement learning based framework for training a natural media agent to learn a rendering policy without human supervision or labeled datasets. The reinforcement learning based framework feeds the natural media agent a training dataset to implicitly learn the rendering policy by exploring a canvas and minimizing a loss function. Once trained, the natural media agent can be applied to any reference image to generate a series (or sequence) of continuous-valued primitive graphic actions, e.g., sequence of painting strokes, that when rendered by a synthetic rendering environment on a canvas, reproduce an identical or transformed version of the reference image subject to limitations of an action space and the learned rendering policy.
    Type: Application
    Filed: October 2, 2023
    Publication date: February 1, 2024
    Inventors: Jonathan BRANDT, Chen FANG, Byungmoon KIM, Biao JIA
  • Publication number: 20240037399
    Abstract: Embodiments of the present disclosure relate to a texture unit circuit in a neural processor circuit. The neural processor circuit includes a tensor access operation circuit with the texture unit circuit, a data processor circuit, and at least one neural engine circuit. The texture unit circuit fetches a source tensor from a system memory by referencing an index tensor in the system memory representing indexing information into the source tensor. The data processor circuit stores an output version of the source tensor obtained from the tensor access operation circuit and sends the output version of the source tensor as multiple of units of input data to the at least one neural engine circuit. The at least one neural engine circuit performs at least convolution operations on the units of input data and at least one kernel to generate output data.
    Type: Application
    Filed: October 10, 2023
    Publication date: February 1, 2024
    Applicant: Apple Inc.
    Inventor: Christopher L. MILLS
  • Publication number: 20240037400
    Abstract: A method for acquiring skills through imitation learning by employing a meta imitation learning framework with structured skill discovery (MILD) is presented. The method includes learning behaviors or tasks, by an agent, from demonstrations: by learning to decompose the demonstrations into segments, via a segmentation component, the segments corresponding to skills that are transferrable across different tasks, learning relationships between the skills that are transferrable across the different tasks, employing, via a graph generator, a graph neural network for learning implicit structures of the skills from the demonstrations to define structured skills, and generating policies from the structured skills to allow the agent to acquire the structured skills for application to one or more target tasks.
    Type: Application
    Filed: October 11, 2023
    Publication date: February 1, 2024
    Inventors: Wenchao Yu, Wei Cheng, Haifeng Chen, Yiwei Sun
  • Publication number: 20240037401
    Abstract: A method for performing contrastive learning for graph tasks and datasets by employing an information-aware graph contrastive learning framework is presented. The method includes obtaining two semantically similar views of a graph coupled with a label for training by employing a view augmentation component, feeding the two semantically similar views into respective encoder networks to extract latent representations preserving both structure and attribute information in the two views, optimizing a contrastive loss based on a contrastive mode by maximizing feature consistency between the latent representations, training a neural network with the optimized contrastive loss, and predicting a new graph label or a new node label in the graph.
    Type: Application
    Filed: October 11, 2023
    Publication date: February 1, 2024
    Inventors: Wei Cheng, Dongkuan Xu, Haifeng Chen
  • Publication number: 20240037402
    Abstract: A method for performing contrastive learning for graph tasks and datasets by employing an information-aware graph contrastive learning framework is presented. The method includes obtaining two semantically similar views of a graph coupled with a label for training by employing a view augmentation component, feeding the two semantically similar views into respective encoder networks to extract latent representations preserving both structure and attribute information in the two views, optimizing a contrastive loss based on a contrastive mode by maximizing feature consistency between the latent representations, training a neural network with the optimized contrastive loss, and predicting a new graph label or a new node label in the graph.
    Type: Application
    Filed: October 11, 2023
    Publication date: February 1, 2024
    Inventors: Wei Cheng, Dongkuan Xu, Haifeng Chen
  • Publication number: 20240037403
    Abstract: A method for performing contrastive learning for graph tasks and datasets by employing an information-aware graph contrastive learning framework is presented. The method includes obtaining two semantically similar views of a graph coupled with a label for training by employing a view augmentation component, feeding the two semantically similar views into respective encoder networks to extract latent representations preserving both structure and attribute information in the two views, optimizing a contrastive loss based on a contrastive mode by maximizing feature consistency between the latent representations, training a neural network with the optimized contrastive loss, and predicting a new graph label or a new node label in the graph.
    Type: Application
    Filed: October 11, 2023
    Publication date: February 1, 2024
    Inventors: Wei Cheng, Dongkuan Xu, Haifeng Chen
  • Publication number: 20240037404
    Abstract: A system, device and method are provided for reducing machine learning models for target hardware. Illustratively, the method includes providing a model, a set of training data, and a training threshold. A search space for reducing the model is determined with a pruning function and a pruning factor. The pruning function is bounded with constraints. Based on the constraints, boundaries for the pruning factor are determined, which boundaries define at least in part the search space. The pruning function increases compression along a depth of the model, and the compression increases are based on the pruning factor. A model is trained into a reduced model by iteratively updating model parameters based on the pruning function and the pruning factor and within the search space, and evaluating the updated model with the training parameters. The method includes providing the reduced model to target hardware.
    Type: Application
    Filed: July 25, 2023
    Publication date: February 1, 2024
    Applicant: Deeplite Inc.
    Inventors: Olivier MASTROPIETRO, Ehsan SABOORI
  • Publication number: 20240037405
    Abstract: Systems and methods for neural machine translation are provided. In one example, a neural machine translation system translates text and comprises processors and a memory storing instructions that, when executed by at least one processor among the processors, cause the system to perform operations comprising, at least, obtaining a text as an input to a neural network system, supplementing the input text with meta information as an extra input to the neural network system, and delivering an output of the neural network system to a user as a translation of the input text, leveraging the meta information for translation.
    Type: Application
    Filed: September 7, 2023
    Publication date: February 1, 2024
    Inventors: Evgeny Matusov, Wenhu Chen, Shahram Khadivi
  • Publication number: 20240037406
    Abstract: A computing system is configured to generate a predictive model during training of a machine learning program using a training data set including a personal data set of a plurality of first users. The predictive model is configured to predict a predicted assessment score of a second user. A test personal data set is generated with at least one different data entry different from the personal data set utilized in predicting the predicted assessment score, the at least one different data entry corresponding to a change in relationship between the computing system and the second user. The predictive model predicts a test predicted assessment score of the second user based on the test personal data set. The computing system takes further action with respect to the second user when a difference between the predicted assessment score and the test predicted assessment score meets or exceeds a threshold value.
    Type: Application
    Filed: July 27, 2022
    Publication date: February 1, 2024
    Applicant: Truist Bank
    Inventors: Dontá Lamar Wilson, Jane Moury Kane, Kenneth William Cluff, Peter Councill, Qing Li, James Xu
  • Publication number: 20240037407
    Abstract: A learning apparatus includes: a score calculation unit that calculates scores by inputting training data with positive or negative labels to a score function; a score specification unit that specifies the lowest one of the scores for the training data with positive labels as a minimum score, and specifies the highest one of the scores for the training data with negative labels as a maximum score; a pair generation unit that selects training data for which the scores are equal to or higher than the minimum and equal to or lower than the maximum, and generates pairs of a positive example and a negative example, and an optimization unit that updates a parameter of the score function through machine learning so as to increase the number of pairs in which a score of training data with positive label is higher than a score of training data with negative label.
    Type: Application
    Filed: August 20, 2020
    Publication date: February 1, 2024
    Applicant: NEC Corporation
    Inventor: Atsushi SATO
  • Publication number: 20240037408
    Abstract: Disclosed are a method and an apparatus for model training and data enhancement, an electronic device and a storage medium. A generative adversarial network model includes a generator and two discriminators, an output of the generator is used as an input of the two discriminators, the method including: generating, by the generator, reference sample data; calculating, by the first discriminator, a first distance between the reference sample data and preset negative sample data; calculating, by the second discriminator, a second distance between negative class data composed of the reference sample data and the preset negative sample data and preset positive sample data; determining an objective function based on the first distance and the second distance; and training the generative adversarial network model by using the objective function until the generative adversarial network model converges, to obtain the generative adversarial network model.
    Type: Application
    Filed: November 15, 2021
    Publication date: February 1, 2024
    Applicant: JINGDONG CITY (BEIJING) DIGITS TECHNOLOGY CO., LTD.
    Inventors: Xinzuo WANG, Yang LIU, Junbo ZHANG, Yu ZHENG
  • Publication number: 20240037409
    Abstract: A method is provided. The method includes generating a first data by using a first decoder model with a first set of target features, wherein the first decoder model is based on the first source domain. The method includes updating a final set of target features and final data based on the generated first data. The method includes generating a second data by using a second decoder model with a second set of target features, wherein the second data that is generated is conditioned on the first set of target features and wherein the second decoder model is based on the second source domain. The method includes updating the final set of target features and final data based on the generated second data. The method includes training a target-domain model using the final data and the final set of target features.
    Type: Application
    Filed: August 21, 2020
    Publication date: February 1, 2024
    Inventors: Selim ICKIN, Caner KILINC, Farnaz MORADI, Alexandros NIKOU, Mats FOLKESSON
  • Publication number: 20240037410
    Abstract: A method for model aggregation in federated learning (FL), a server, a device, and a storage medium are suggested, which relate to the field of artificial intelligence (AI) technologies such as machine learning. A specific implementation solution involves: acquiring a data not identically and independently distributed (Non-IID) degree value of each of a plurality of edge devices participating in FL; acquiring local models uploaded by the edge devices; and performing aggregation based on the data Non-IID degree values of the edge devices and the local models uploaded by the edge devices to obtain a global model.
    Type: Application
    Filed: February 13, 2023
    Publication date: February 1, 2024
    Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.
    Inventors: Ji LIU, Beichen MA, Dejing DOU
  • Publication number: 20240037411
    Abstract: A method for training a model using a meta-learning includes training a base learning model; training a loss meta-learning model used as a loss function of the base learning model for each task; and training a meta-learning model used to optimize a parameter of the loss meta-learning model.
    Type: Application
    Filed: December 15, 2022
    Publication date: February 1, 2024
    Applicants: Hyundai Motor Company, KIA CORPORATION, Seoul National University R&DB Foundation
    Inventors: Jaesik MIN, Kyoung Mu LEE, Sungyong BAIK, Janghoon CHOI, Heewon KIM, Dohee CHO
  • Publication number: 20240037412
    Abstract: A neural network generation device that generates a neural network execution model for performing neural network operations, the neural network generation device including an execution model generation unit that generates the neural network execution model based on hardware information regarding hardware in which the neural network execution model is running and network information regarding the neural network, and a software generation unit that generates software for running neural network hardware obtained by installing the neural network model in the hardware.
    Type: Application
    Filed: October 19, 2021
    Publication date: February 1, 2024
    Inventors: Junichi KANAI, Chuta YAMAOKA
  • Publication number: 20240037413
    Abstract: The present invention proposes the use of an optimization tool based on Genetic Algorithm for the optimization of the drainage mesh, that is, the simultaneous optimization of the quantity, location and length of producing and injecting wells. Said optimization tool provides a robust implementation of a computational method to deal with realistic well positioning problems with arbitrary trajectories, complex models and linear and nonlinear constraints. Said optimization tool uses a commercial reservoir simulator as an evaluation function without using proxies to replace the complete numerical model. A net present value (NPV) calculation is also provided as a criterion for obtaining the optimized drainage mesh.
    Type: Application
    Filed: July 26, 2023
    Publication date: February 1, 2024
    Inventor: MARCO ANTONIO CARDOSO
  • Publication number: 20240037414
    Abstract: An assistant executing at, at least one processor, is described that determines content for a conversation with a user of a computing device and selects, based on the content and information associated with the user, a modality to signal initiating the conversation with the user. The assistant is further described that causes, in the modality, a signaling of the conversation with the user.
    Type: Application
    Filed: October 9, 2023
    Publication date: February 1, 2024
    Inventors: Vikram Aggarwal, Deniz Binay
  • Publication number: 20240037415
    Abstract: Systems and methods may predict whether a user will abandon an application. Initially, different features are extracted from a time series of numerical values rendered by the application. A machine learning model is trained using a supervised approach on the extracted features to map the known and labeled outputs. In this supervised approach, the output may be binary with a “0”-label for a user that has left the application in the middle of a task and a “1”-label for the user who has used the application to finish the task. During the deployment, the trained model may be called to predict whether the user will abandon the application based on time series of numerical values retrieved in real time. If an abandonment is predicted, a customized message is generated and presented on the user's device.
    Type: Application
    Filed: July 27, 2022
    Publication date: February 1, 2024
    Applicant: INTUIT INC.
    Inventor: Prateek ANAND
  • Publication number: 20240037416
    Abstract: A computer-implemented system and method relate to test-time adaptation of a machine learning system from a source domain to a target domain. Sensor data is obtained from a target domain. The machine learning system generates prediction data based on the sensor data. Pseudo-reference data is generated based on a gradient of a predetermined function evaluated with the prediction data. Loss data is generated based on the pseudo-reference data and the prediction data. One or more parameters of the machine learning system is updated based on the loss data. The machine learning system is configured to perform a task in the target domain after the one or more parameters has been updated.
    Type: Application
    Filed: July 19, 2022
    Publication date: February 1, 2024
    Inventors: Mingjie SUN, Sachin GOYAL, Aditi RAGHUNATHAN, Jeremy KOLTER, Wan-Yi LIN
  • Publication number: 20240037417
    Abstract: Systems and methods of context-aware caller identification via machine learning techniques are disclosed.
    Type: Application
    Filed: July 26, 2022
    Publication date: February 1, 2024
    Inventors: Lin Ni Lisa Cheng, Shabnam Kousha, Tyler Maiman, Asher Smith-Rose, Joshua Edwards
  • Publication number: 20240037418
    Abstract: A method of self-learning actions for an automated co-browse session according to an embodiment include initiating an interaction between a user and a chat bot, determining a user intent of the user based on the interaction between the user and the chat bot, routing the interaction to a human contact center agent for a co-browse session between the user and the human contact center agent, storing a plurality of actions performed by the human contact center agent during the co-browse session to a data store, and performing machine learning to determine an optimal solution for resolving the user intent based on an analysis of the plurality of actions performed by the human contact center agent during the co-browse session.
    Type: Application
    Filed: July 27, 2022
    Publication date: February 1, 2024
    Inventors: Asmitha Durairaj, Monisha Padmavathi Ragavan, Santhos Palani Vell Rajan Manickam, Vinoth Subramaniam, Mohamed Uvaiz Anwar Batcha, Praveen Kumar Anandadoss, Tony Thazhekkaden
  • Publication number: 20240037419
    Abstract: In some implementations, a monitoring device may obtain a plurality of time-series data streams respectively associated with a plurality of resources. The monitoring device may generate, using a plurality of machine learning models and based on the plurality of time-series data streams, a plurality of sets of multi-step forecast values, wherein each set of multi-step forecast values is associated with the plurality of resources. The monitoring device may determine, based on the plurality of sets of multi-step forecast values, a set of particular multi-step forecast values associated with the plurality of resources. The monitoring device may cause, based on the set of particular multi-step forecast values, one or more actions to be performed. In some implementations, the monitoring device may determine, based on the plurality of time-series data streams and the plurality of sets of multi-step forecast values, that a correlation exists between a first resource and a second resource.
    Type: Application
    Filed: August 1, 2022
    Publication date: February 1, 2024
    Inventors: Sabyasachi MUKHOPADHYAY, Rakshith N, Sanjeev Kumar MISHRA, Pooja Sambhaji AYANILE, Darshan Tirumale DHANARAJ, Subhabrata BANERJEE, Sarath GOLLAPUDI
  • Publication number: 20240037420
    Abstract: A system includes a memory storing computer-readable instructions and at least one processor to execute the instructions to receive a query comprising one or more words having a particular sequence, determine a three-dimensional representation of available information associated with the query based on a plurality of information banks, each information bank comprising a layer of available information associated with the query, evaluate the query using the three-dimensional representation of available information associated with the query, the three-dimensional representation of available information having a plurality of terms, each term comprising an identifier, a value, and zero or more related terms, generate a response to the query using the three-dimensional representation of available information, and convert the response to the query into a format for storage.
    Type: Application
    Filed: May 5, 2023
    Publication date: February 1, 2024
    Inventors: Rommel MARTINEZ, Robert PINEDA
  • Publication number: 20240037421
    Abstract: A system for knowledge discovery includes a processor and a memory. The memory includes instructions which, when executed by the processor, cause the system to: access a reference case of a plurality of cases; generate argumentation explaining a phenomenon of the reference case by developing a predictive model; generate a knowledge-based generalization of the argumentation; apply the argumentation to a plurality of cases similar to the reference case based on knowledge-based search and classification; split the plurality of similar cases into a plurality of favoring cases and a plurality of disfavoring cases; select a disfavoring case based on a similarity of factors; determine what factors were not taken into account in generating the argumentation; and generate a hypothesis-driven explanation theory based on comparing one or more features of the reference case to one or more features of the most disfavoring case.
    Type: Application
    Filed: July 28, 2023
    Publication date: February 1, 2024
    Inventor: Gheorghe Tecuci
  • Publication number: 20240037422
    Abstract: A method, implemented by a computing machine, for constructing a knowledge base. The method includes, while using a terminal, at least one update to the knowledge base based on information extracted from useful application areas of a digital image of a screenshot of at least part of the rendering from a screen of the terminal.
    Type: Application
    Filed: November 24, 2021
    Publication date: February 1, 2024
    Inventors: Sonia LAURENT, Cédric FLOURY
  • Publication number: 20240037423
    Abstract: An information processing apparatus includes an index value calculation module and a parameter determination module. The index value calculation module calculates values of preset indexes for each of adjustment parameter sets to calculate regression coefficients which are used to derive a predicted value from past data. The parameter determination module selects an appropriate adjustment parameter set based on the index values calculated for each of the adjustment parameter sets and index values of neighborhood adjustment parameter sets with respect to the interested each adjustment parameter set.
    Type: Application
    Filed: July 7, 2023
    Publication date: February 1, 2024
    Applicant: AZBIL CORPORATION
    Inventor: Sei NAGASHIMA
  • Publication number: 20240037424
    Abstract: The embodiments of the present disclosure provide methods and Internet of Things (IoT) system for managing an operation progress of a smart gas pipeline network. The method includes: obtaining a construction type and a progress sequence of a gas operation based on a smart terminal and a sensing unit; predicting a future operation progress at a future moment through a progress prediction model based on the construction type and the progress sequence, the progress prediction model being a machine learning model; generating a first prompt message and a second prompt message based on the future operation progress, the first prompt message including the progress reminder data of the gas operation, and the second prompt message including an approach plan of a gas associated object; and sending the first prompt message to a gas operator and sending the second prompt message to the gas associated object.
    Type: Application
    Filed: October 10, 2023
    Publication date: February 1, 2024
    Applicant: CHENGDU QINCHUAN IOT TECHNOLOGY CO., LTD.
    Inventors: Zehua SHAO, Yong LI, Bin LIU
  • Publication number: 20240037425
    Abstract: Aspects of the present disclosure provide techniques for machine learning and rules integration. Embodiments include receiving input values corresponding to a subset of a set of input variables associated with an automated determination. Embodiments include generating a directed acyclic graph (DAG) representing a set of constraints corresponding to the set of input variables. The set of constraints relate to one or more machine learning models and one or more rules. Embodiments include receiving one or more outputs from the one or more machine learning models based on one or more of the input values. Embodiments include determining outcomes for the one or more rules based on at least one of the input values. Embodiments include populating the DAG based on the input values, the one or more outputs, and the outcomes. Embodiments include making the automated determination based on logic represented by the DAG.
    Type: Application
    Filed: May 8, 2023
    Publication date: February 1, 2024
    Inventors: Sricharan Kallur Palli KUMAR, Conrad DE PEUTER, Efraim David FEINSTEIN, Nagaraj JANARDHANA, Yi Xu NG, Ian Andrew SEBANJA
  • Publication number: 20240037426
    Abstract: An Automatic Dependent Surveillance Broadcast (ADS-B) system may include a plurality of ADS-B terrestrial stations, with each ADS-B terrestrial station comprising an antenna and wireless circuitry associated therewith defining a station gain pattern. The system may further include a controller including a variational autoencoder (VAE) configured to compress station pattern data from the plurality of ADS-B terrestrial stations, create a normal distribution of the compressed data in a latent space of the VAE, and decompress the compressed station pattern data from the latent space. The controller may also include a processor coupled to the VAE and configured to process the decompressed station pattern data using a probabilistic model selected from among different probabilistic models based upon a game theoretic reward matrix, determine an anomaly from the processed decompressed station pattern data, and generate an alert (e.g., a station specific alert) based upon the determined anomaly.
    Type: Application
    Filed: July 26, 2022
    Publication date: February 1, 2024
    Inventors: MARK D. RAHMES, KEVIN L. FOX, GRAN ROE, CHRISTOPHER JASON BERGER, RALPH SMITH, TIMOTHY B. FAULKNER, ROBERT KONCZYNSKI, KEVIN R. NIEWOEHNER
  • Publication number: 20240037427
    Abstract: A computing system may generate a first set of importance metrics (e.g., scores or values) for a model. The importance metrics may be generated using an explainable artificial intelligence technique, and an individual importance metric may indicate how influential a corresponding feature is for a decision made by a model. The computing system may determine an important feature and create a modified dataset by removing the important feature from the dataset. The computing system may train the model on the modified dataset and evaluate the performance of the model to determine the effect of removing the feature (e.g., which may indicate how important the feature is to output generated by the model). This process may be repeated for additional features and additional performance metrics may be obtained.
    Type: Application
    Filed: July 26, 2022
    Publication date: February 1, 2024
    Applicant: Capital One Services, LLC
    Inventors: Samuel SHARPE, Christopher Bayan BRUSS, Brian BARR, Sahil VERMA, Jocelyn HUANG
  • Publication number: 20240037428
    Abstract: The invention is direct towards generating an expert template. The expert template is associated with an expert who can help guide a user. A user is associated with user goal data and a user goal. A user goal is an objective that the user wants to complete. A user is matched with an expert that matches the expert's field of expertise with the user's goals. An expert may provide input to the user regarding guidance and goals.
    Type: Application
    Filed: July 25, 2022
    Publication date: February 1, 2024
    Applicant: Gravystack, Inc.
    Inventors: Scott Donnell, Travis Adams, Chad Willardson
  • Publication number: 20240037429
    Abstract: A method for manipulating an intermediate representation of a modular packet-processing program is provided. The method includes receiving a plurality of modules configured to be conditionally executed, the plurality of modules including at least two parsers, ordering, topologically, at least two extracted header instances in a state of each of the at least two parsers, mapping the at least two header instances to use a common memory block, constructing a common parser directed-acyclic-graph (DAG), synthesizing a bitwise operation on a header instance validity bit and a packet validity bit of a common state in the common parser DAG, and outputting the common parser DAG into the intermediate representation.
    Type: Application
    Filed: February 15, 2023
    Publication date: February 1, 2024
    Inventor: Hardik Soni
  • Publication number: 20240037430
    Abstract: According to an embodiment, an information processing system solves a combinatorial optimization problem. The information processing system includes an Ising machine and a host unit. The Ising machine is hardware configured to perform a search process for searching for the ground state of an Ising model that represents the combinatorial optimization problem. The host unit is hardware connected to the Ising machine via an interface and configured to control the Ising machine. In the search process, for each of a plurality of Ising spins, the Ising machine alternately repeats an auxiliary variable update process for updating an auxiliary variable by a main variable and a main variable update process for updating the main variable by the auxiliary variable multiple times. Prior to the search process, the host unit transmits, to the Ising machine, an initial value of the auxiliary variable corresponding to each of the plurality of Ising spins.
    Type: Application
    Filed: October 9, 2023
    Publication date: February 1, 2024
    Applicant: KABUSHIKI KAISHA TOSHIBA
    Inventors: Ryo HIDAKA, Kosuke TATSUMURA, Masaya YAMASAKI, Yohei HAMAKAWA, Hayato GOTO
  • Publication number: 20240037431
    Abstract: Among other things, an apparatus comprises quantum units; and couplers among the quantum units. Each coupler is configured to couple a pair of quantum units according to a quantum Hamiltonian characterizing the quantum units and the couplers. The quantum Hamiltonian includes quantum annealer Hamiltonian and a quantum governor Hamiltonian. The quantum annealer Hamiltonian includes information bearing degrees of freedom. The quantum governor Hamiltonian includes non-information bearing degrees of freedom that are engineered to steer the dissipative dynamics of information bearing degrees of freedom.
    Type: Application
    Filed: October 10, 2023
    Publication date: February 1, 2024
    Inventors: Masoud Mohseni, Hartmut Neven
  • Publication number: 20240037432
    Abstract: Examples relating to quantum computing networks are provided. In one example, data indicative of a quantum computing device joining a quantum computing network is received. A plurality of quantum simulator nodes are generated for the quantum computing device. Each quantum simulator node simulates one of a plurality of different operating states of the quantum computing device. Each of the quantum simulator nodes is stored as an execution node of the quantum computing network for execution of a quantum service.
    Type: Application
    Filed: July 27, 2022
    Publication date: February 1, 2024
    Inventors: Stephen Coady, Leigh Griffin
  • Publication number: 20240037433
    Abstract: Disclosed are a method and device for constructing a quantum circuit of a QRAM architecture, the QRAM architecture being configured for accessing data and being a binary tree structure, the method including: partitioning the binary tree structure into basic circuit structures, wherein a basic circuit structure comprises address bits and data bits of one subtree node and data bits of two child nodes in the lower layer of the one subtree node; determining qubits required for a basic quantum circuit to be constructed, according to qubits included in the basic circuit structure; determining an input and an output of the basic quantum circuit to be constructed, according to action relationships between the qubits required for the basic quantum circuit to be constructed; and constructing a basic quantum circuit corresponding to the basic circuit structure, according to the input and the output using the required qubits and quantum logic gates.
    Type: Application
    Filed: May 26, 2021
    Publication date: February 1, 2024
    Applicant: Origin Quantum Computing Technology Co., Ltd.
    Inventors: YE LI, Ningbo An Hefei, Menghan Dou
  • Publication number: 20240037434
    Abstract: A method for simulating a quantum-capacitance response of a material configuration comprises (a) constructing a non-interacting Hamiltonian for the material configuration based on input data; (b) computing a natural-orbitals basis for each of a plurality of parts of the material configuration under the non-interacting Hamiltonian; (c) projecting the non-interacting Hamiltonian in the natural-orbitals basis to obtain a non-interacting quantum-mechanical description for each part; (d) constructing an interacting Hamiltonian by adding an electron-interaction term to the non-interacting Hamiltonian for each of the plurality of parts; (e) for each of a plurality of representative points in a sample space of at least one tunable parameter of the material configuration, using a sums-of-Gaussians procedure to assemble a basis of Gaussian states for approximating low-energy eigenstates of the material configuration under the interacting Hamiltonian; (f) for each of a plurality of vicinities of representative points in
    Type: Application
    Filed: November 7, 2022
    Publication date: February 1, 2024
    Applicant: Microsoft Technology Licensing, LLC
    Inventors: Samuel BOUTIN, Roman Bela BAUER
  • Publication number: 20240037435
    Abstract: A computation device generates a plan that controls an oscillator configured to perform parametric oscillation such that an intensity of a pump signal that is input to the oscillator increases from a first value according to an elapsed time and then decreases to a second value, and a magnitude of a detuning between a resonance frequency of the oscillator and an oscillation frequency of the oscillator increases from a third value according to the elapsed time and then decreases to a fourth value. The computation device generates a quantum state of the oscillator by controlling the oscillator based on the plan. The computation device performs computation using the generated quantum state.
    Type: Application
    Filed: July 17, 2023
    Publication date: February 1, 2024
    Applicant: NEC Corporation
    Inventors: Yuki Susa, Aiko Yamaguchi
  • Publication number: 20240037436
    Abstract: A system for processing a quantum task, a method, a device and a storage medium are provided. The system includes: a user terminal, configured to acquire basic measurement and control parameters of a superconducting quantum computer, generate a quantum task consisting of a quantum pulse and a quantum pulse gate based on the basic measurement and control parameters and an intended task purpose, and send the quantum task to a quantum hardware client; the quantum hardware client, configured to parse the quantum task into a queue of quantum pulses arranged in a time sequence, and send the queue of quantum pulses to the superconducting quantum computer; and the superconducting quantum computer, configured to execute quantum pulse instructions in the queue of quantum pulses in the time sequence, and return an obtained task result to the user terminal.
    Type: Application
    Filed: October 9, 2023
    Publication date: February 1, 2024
    Inventors: Zelin MENG, Shusen LIU, Xueyi GUO, Zixian YAN, Wenxue ZHANG, Yang HE
  • Publication number: 20240037437
    Abstract: A quantum information processing device includes a control unit controlling a quantum bit array, and a common control gate line capable of controlling a plurality of quantum bits, the common control gate line is commonly connected to each of the plurality of transistors, and the control unit performs control such that the number of quantum bits operated in the quantum bit array is less than or equal to half the total number of transistors.
    Type: Application
    Filed: February 14, 2023
    Publication date: February 1, 2024
    Inventor: Go SHINKAI
  • Publication number: 20240037438
    Abstract: Disclosed are a superconducting quantum chip structure and a fabrication method for a superconducting quantum chip. The superconducting quantum chip structure includes a first structural member, a second structural member, and a support and connection member, where the first structural member is provided with a qubit, a read cavity, and a first connection terminal, the qubit is coupled to the read cavity, and the qubit is electrically connected to the first connection terminal; the second structural member is provided with a signal transmission line and a second connection terminal electrically connected to each other; and two ends of the support and connection member are electrically connected to the first connection terminal and the second connection terminal, respectively, and the support and connection member is configured to transmit a control signal received on the signal transmission line to the qubit.
    Type: Application
    Filed: May 9, 2023
    Publication date: February 1, 2024
    Applicant: ORIGIN QUANTUM COMPUTING TECHNOLOGY CO., LTD.
    Inventor: Yongjie ZHAO
  • Publication number: 20240037439
    Abstract: Systems/techniques that facilitate quantum system selection via coupling map comparison are provided. In various embodiments, a system can access a quantum machine learning (QML) model. In various aspects, the system can identify, from a set of quantum computing systems, a quantum computing system for the QML model, based on a comparison between a first coupling map of the quantum computing system and a second coupling map on which the QML model was trained. If the second coupling map topologically matches the first coupling map or topologically matches a subgraph of the first coupling map, the system can execute the QML model on the quantum computing system. Otherwise, the system can adjust the QML model and can accordingly execute the adjusted QML model on the quantum computing system.
    Type: Application
    Filed: July 27, 2022
    Publication date: February 1, 2024
    Inventors: John S. Werner, Vladimir Rastunkov, Frederik Frank Flöther
  • Publication number: 20240037440
    Abstract: Embodiments of the present disclosure provide techniques for performing a quantum computing-based diamond dependency analysis. A classical diamond dependency service may analyze a service and determine a set of dependencies that the service requires to execute. The classical DDS may then generate a quantum assembly language (QASM) file comprising a diamond dependency algorithm (DDA) and a mapping of a configuration file of the service and a configuration file of each of the set of dependencies to a respective qubit among a plurality of qubits. The classical DDS may interface with one or more quantum DDSs (QDDSs) that are each part of a respective quantum environment in order to determine qubits that are available to be mapped to the configuration files of the service and its dependencies. The classical DDS may execute the QASM file using the one or more QDDSs to detect one or more diamond dependencies.
    Type: Application
    Filed: July 26, 2022
    Publication date: February 1, 2024
    Inventors: Leigh Griffin, Stephen Coady
  • Publication number: 20240037441
    Abstract: Disclosed are techniques for training a machine learning model. In an aspect, a user equipment (UE) receives, from a network entity, one or more selection criteria for determining whether the UE is to participate in training the machine learning model, determines whether the UE satisfies the one or more selection criteria during a first period of time, and transmits, to the network entity, after a second period of time, updated parameters for the machine learning model, wherein the machine learning model is updated during the second period of time based on a determination that the UE satisfies the one or more selection criteria.
    Type: Application
    Filed: August 1, 2022
    Publication date: February 1, 2024
    Inventors: Marwen ZORGUI, Srinivas YERRAMALLI, Mohammed Ali Mohammed HIRZALLAH, Taesang YOO, Xiaoxia ZHANG, Mohammad Tarek FAHIM, Rajat PRAKASH, Roohollah AMIRI
  • Publication number: 20240037442
    Abstract: A method includes receiving a first value associated with a first input parameter of a model. The method further includes receiving a first plurality of values associated with a second input parameter of the model. The method further includes providing to the model the first value and the first plurality of values. The method further includes receiving a first plurality of outputs from the model. The method further includes preparing the first plurality of outputs for presentation via a presentation element of a graphical user interface. The presentation element includes two axes. The first axis is associated with a first property of a first feature associated with the output from the model. The second axis is associated with a second property of the first feature.
    Type: Application
    Filed: July 26, 2022
    Publication date: February 1, 2024
    Inventor: Dermot Patrick Cantwell
  • Publication number: 20240037443
    Abstract: The present application discloses a method, system, and computer system for detecting parked domains. The method includes obtaining, by one or more processors, a set of webpages corresponding to a plurality of domains, extracting a plurality of features based on the set of webpages, detecting parked domains based on the plurality of features using a machine learning model, and periodically applying automatic signature generation to detect a new pattern of parked domains without retraining the machine learning model.
    Type: Application
    Filed: July 29, 2022
    Publication date: February 1, 2024
    Inventors: Zeyu You, Wei Wang, Yu Zhang
  • Publication number: 20240037444
    Abstract: An apparatus, method and computer program product are provided for predicting improper parking events within electric vehicle charging locations. In one example, the apparatus receives input data indicating whether a first charging station is being used and a first pattern of frequency in which the first charging station is used. The apparatus generates an output data indicating a likelihood in which a first vehicle is occupying a first parking space designated for the first charging station and is electrically disconnected from the first charging station. The apparatus generates the output data as a function of the input data by using historical data indicating events in which second vehicles occupied second parking spaces designated for second charging stations and were electrically disconnected from the second charging stations. The historical data indicate a second pattern of frequency in which each of the second charging stations is used.
    Type: Application
    Filed: July 29, 2022
    Publication date: February 1, 2024
    Applicant: HERE GLOBAL B.V.
    Inventor: Jerome BEAUREPAIRE
  • Publication number: 20240037445
    Abstract: Systems and methods for pessimistic offline reinforcement learning are described herein. In one example, a method for performing offline reinforcement learning determines when sampled states are out of distribution, assigns high probability weights to the sampled states that are out of distribution, generates a fitted Q-function by solving an optimization problem with a minimization term and a maximization term, estimates a Q-value using the fitted Q-function by estimating the overall expected reward assuming the agent is in the present state and performs a present action, and updates the policy according to an existing reinforcement learning algorithm. The minimization term penalizes an overall expected reward when a present state is out of distribution. The maximization term cancels the minimization term when the present state is an in-distribution state.
    Type: Application
    Filed: October 19, 2022
    Publication date: February 1, 2024
    Applicants: Denso International America, Inc., The Regents of the University of California, DENSO CORPORATION
    Inventors: Minglei Huang, Jinning Li, Chen Tang, Masayoshi Tomizuka, Wei Zhan
  • Publication number: 20240037446
    Abstract: The disclosure relates to a method for training a classifier to determine a handheld machine tool device state, comprising the following steps:—providing a handheld machine tool; —providing at least one sensor; —operating the handheld machine tool continuously; —terminating the continuous operation, in particular in the event of damage occurring; —capturing sensor data during the continuous operation; —extracting features on the basis of the sensor data; —ascertaining at least two handheld machine tool device states on the basis of the extracted features.
    Type: Application
    Filed: June 23, 2021
    Publication date: February 1, 2024
    Inventors: Andreas Vogt, Matthias Tauber, Frank Wolter
  • Publication number: 20240037447
    Abstract: One aspect of the invention relates to a device for training a reinforcement learning agent to control an autonomous system, wherein the device is designed to detect the environment of the autonomous system, to detect at least one object in the environment of the autonomous system that can be compared to the autonomous system, to detect a behaviour of the at least one object that can be compared to the autonomous system, and to train the reinforcement learning agent in accordance with the detected behaviour of the at least one object that can be compared to the autonomous system.
    Type: Application
    Filed: June 14, 2021
    Publication date: February 1, 2024
    Inventors: Joschka BOEDECKER, Maria HUEGLE, Gabriel KALWEIT, Moritz WERLING