Patents by Inventor Mark Wegman

Mark Wegman 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).

  • Publication number: 20250077888
    Abstract: Predicting local layout effects using a variational autoencoder with integrated regression and classification network including identifying a vector of features and a vector of output metrics from a dataset; performing basic training of a neural network machine learning variational autoencoder (VAE) combined with a regression network using the vector of features and the vector of output targets constrained to a latent space of the VAE; performing interpolation training of the VAE and combined regression network; determining a set of influential features of an integrated circuit layout based on an input gradient using an output of the VAE and combined regression network with interpolation training; using the set of influential features as input into a parallel neural network to generate a function for each influential feature; and creating a compact model to calculate local layout effects based on the functions for each influential feature.
    Type: Application
    Filed: September 1, 2023
    Publication date: March 6, 2025
    Inventors: MICHAEL DANIEL MONKOWSKI, MICHAEL KAZDA, MARK WEGMAN, RICHARD ANDRE WACHNIK
  • Publication number: 20240330656
    Abstract: A generator is configured to generate a domain-independent representation of an input data sample, an encoder is configured to generate a domain-dependent representation of the input data sample, and a decoder is configured to ensure that a combination of the domain-independent representation and the domain-dependent representation contains sufficient information to reconstruct the input data sample. A discriminator is configured to attempt to determine an originating domain of the domain-independent representation and a classifier is configured to classify the input data sample based on the domain-independent representation of the input data sample.
    Type: Application
    Filed: March 31, 2023
    Publication date: October 3, 2024
    Inventors: Mark Wegman, Yuhai Tu, Xuan-Hong Dang, Ankush Singla, Adrian Shuai Li
  • Patent number: 11972321
    Abstract: Systems, computer-implemented methods, and computer program products to facilitate quantum computing job scheduling are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store the quantum computing jobs based on the run order. In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity.
    Type: Grant
    Filed: March 11, 2021
    Date of Patent: April 30, 2024
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Patent number: 11687783
    Abstract: A training method, system, and computer program product include training a neural network including at least one of using norm-pooling as a non-linear function, using a two-sided ReLU as a non-linear function, and increasing a confidence gap and further training such that the network comprises a non-expansive network.
    Type: Grant
    Filed: February 4, 2019
    Date of Patent: June 27, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Haifeng Qian, Mark Wegman
  • Patent number: 11645203
    Abstract: Techniques facilitating cached result use through quantum gate rewrite are provided. In one example, a computer-implemented method comprises converting, by a device operatively coupled to a processor, an input quantum circuit to a normalized form, resulting in a normalized quantum circuit; detecting, by the device, a match between the normalized quantum circuit and a cached quantum circuit among a set of cached quantum circuits; and providing, by the device, a cached run result of the cached quantum circuit based on the detecting.
    Type: Grant
    Filed: December 28, 2020
    Date of Patent: May 9, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky, Jay M. Gambetta, Ali Javadiabhari, David C. Mckay
  • Patent number: 11625554
    Abstract: A training method, system, and computer program product include training a neural network including using two-sided ReLU as a non-linear function or norm-pooling as a non-linear function and increasing a confidence gap.
    Type: Grant
    Filed: February 4, 2019
    Date of Patent: April 11, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Haifeng Qian, Mark Wegman
  • Patent number: 11556794
    Abstract: Techniques for improved neural network modeling are provided. In one embodiment, a system comprises a memory that stores computer-executable components and a processor that executes the components. The computer-executable components can comprise a loss function logic component that determines a penalty based on a training term, the training term being a function of a relationship between an output scalar value of a first neuron of a plurality of neurons of a neural network model, a plurality of input values from the first neuron, and one or more tunable weights of connections between the plurality of neurons; an optimizer component that receives the penalty from the loss function component, and changes one or more of the tunable weights based on the penalty; and an output component that generates one or more output values indicating whether a defined pattern is detected in unprocessed input values received at the neural network evaluation component.
    Type: Grant
    Filed: December 14, 2017
    Date of Patent: January 17, 2023
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Haifeng Qian, Mark Wegman
  • Patent number: 11521014
    Abstract: A training method, system, and computer program product include computing a matrix norm over a product of a weight matrix and a transpose of the weight matrix and using the matrix norm to constrain the L2 non-expansive neural network.
    Type: Grant
    Filed: February 4, 2019
    Date of Patent: December 6, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: Haifeng Qian, Mark Wegman
  • Patent number: 11475189
    Abstract: A method for adaptive error correction in quantum computing includes executing a calibration operation on a set of qubits, the calibration operation determining an initial state of a quantum processor. In an embodiment, the method includes estimating, responsive to determining an initial state of the quantum processor, a runtime duration for a quantum circuit design corresponding to a quantum algorithm, the quantum processor configured to execute the quantum circuit design. In an embodiment, the method includes computing an error scenario for the quantum circuit design. In an embodiment, the method includes selecting, using the error scenario and the initial state of the quantum processor, a quantum error correction approach for the quantum circuit design. In an embodiment, the method includes transforming the quantum algorithm into the quantum circuit design, the quantum circuit design including a set of quantum logic gates.
    Type: Grant
    Filed: April 20, 2021
    Date of Patent: October 18, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Patent number: 11443086
    Abstract: A method for adaptive error correction in quantum computing includes executing a calibration operation on a set of qubits, the calibration operation determining an initial state of a quantum processor. In an embodiment, the method includes estimating, responsive to determining an initial state of the quantum processor, a runtime duration for a quantum circuit design corresponding to a quantum algorithm, the quantum processor configured to execute the quantum circuit design. In an embodiment, the method includes computing an error scenario for the quantum circuit design. In an embodiment, the method includes selecting, using the error scenario and the initial state of the quantum processor, a quantum error correction approach for the quantum circuit design. In an embodiment, the method includes transforming the quantum algorithm into the quantum circuit design, the quantum circuit design including a set of quantum logic gates.
    Type: Grant
    Filed: April 20, 2021
    Date of Patent: September 13, 2022
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Publication number: 20220100847
    Abstract: A computer system, computer program product, and computer implemented method to enhance robustness an artificial neural network through obfuscation. One or more high frequency and low amplitude elements are added to the artificial neural network. The added elements provide a defense mechanism to the artificial network, thereby functioning as a security mechanism against an adversarial attack.
    Type: Application
    Filed: September 29, 2020
    Publication date: March 31, 2022
    Applicant: International Business Machines Corporation
    Inventors: Mark Wegman, Haifeng Qian, Ian Michael Molloy, Taesung Lee, Chiayi Hsu
  • Publication number: 20210240893
    Abstract: A method for adaptive error correction in quantum computing includes executing a calibration operation on a set of qubits, the calibration operation determining an initial state of a quantum processor. In an embodiment, the method includes estimating, responsive to determining an initial state of the quantum processor, a runtime duration for a quantum circuit design corresponding to a quantum algorithm, the quantum processor configured to execute the quantum circuit design. In an embodiment, the method includes computing an error scenario for the quantum circuit design. In an embodiment, the method includes selecting, using the error scenario and the initial state of the quantum processor, a quantum error correction approach for the quantum circuit design. In an embodiment, the method includes transforming the quantum algorithm into the quantum circuit design, the quantum circuit design including a set of quantum logic gates.
    Type: Application
    Filed: April 20, 2021
    Publication date: August 5, 2021
    Applicant: International Business Machines Corporation
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Publication number: 20210201189
    Abstract: Systems, computer-implemented methods, and computer program products to facilitate quantum computing job scheduling are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store the quantum computing jobs based on the run order. In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity.
    Type: Application
    Filed: March 11, 2021
    Publication date: July 1, 2021
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Patent number: 11048839
    Abstract: A method for adaptive error correction in quantum computing includes executing a calibration operation on a set of qubits, the calibration operation determining an initial state of a quantum processor. In an embodiment, the method includes estimating, responsive to determining an initial state of the quantum processor, a runtime duration for a quantum circuit design corresponding to a quantum algorithm, the quantum processor configured to execute the quantum circuit design. In an embodiment, the method includes computing an error scenario for the quantum circuit design. In an embodiment, the method includes selecting, using the error scenario and the initial state of the quantum processor, a quantum error correction approach for the quantum circuit design. In an embodiment, the method includes transforming the quantum algorithm into the quantum circuit design, the quantum circuit design including a set of quantum logic gates.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: June 29, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Patent number: 10997519
    Abstract: Systems, computer-implemented methods, and computer program products to facilitate quantum computing job scheduling are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a scheduler component that can determine a run order of quantum computing jobs based on one or more quantum based run constraints. The computer executable components can further comprise a run queue component that can store the quantum computing jobs based on the run order. In an embodiment, the scheduler component can determine the run order based on availability of one or more qubits comprising a defined level of fidelity.
    Type: Grant
    Filed: November 29, 2018
    Date of Patent: May 4, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Publication number: 20210117324
    Abstract: Techniques facilitating cached result use through quantum gate rewrite are provided. In one example, a computer-implemented method comprises converting, by a device operatively coupled to a processor, an input quantum circuit to a normalized form, resulting in a normalized quantum circuit; detecting, by the device, a match between the normalized quantum circuit and a cached quantum circuit among a set of cached quantum circuits; and providing, by the device, a cached run result of the cached quantum circuit based on the detecting.
    Type: Application
    Filed: December 28, 2020
    Publication date: April 22, 2021
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky, Jay M. Gambetta, Ali Javadiabhari, David C. Mckay
  • Patent number: 10901896
    Abstract: Techniques facilitating cached result use through quantum gate rewrite are provided. In one example, a computer-implemented method comprises converting, by a device operatively coupled to a processor, an input quantum circuit to a normalized form, resulting in a normalized quantum circuit; detecting, by the device, a match between the normalized quantum circuit and a cached quantum circuit among a set of cached quantum circuits; and providing, by the device, a cached run result of the cached quantum circuit based on the detecting.
    Type: Grant
    Filed: November 27, 2018
    Date of Patent: January 26, 2021
    Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky, Jay M. Gambetta, Ali Javadiabhari, David C. Mckay
  • Publication number: 20200311220
    Abstract: A method for adaptive error correction in quantum computing includes executing a calibration operation on a set of qubits, the calibration operation determining an initial state of a quantum processor. In an embodiment, the method includes estimating, responsive to determining an initial state of the quantum processor, a runtime duration for a quantum circuit design corresponding to a quantum algorithm, the quantum processor configured to execute the quantum circuit design. In an embodiment, the method includes computing an error scenario for the quantum circuit design. In an embodiment, the method includes selecting, using the error scenario and the initial state of the quantum processor, a quantum error correction approach for the quantum circuit design. In an embodiment, the method includes transforming the quantum algorithm into the quantum circuit design, the quantum circuit design including a set of quantum logic gates.
    Type: Application
    Filed: March 29, 2019
    Publication date: October 1, 2020
    Applicant: International Business Machines Corporation
    Inventors: John A. Gunnels, Mark Wegman, David Kaminsky
  • Publication number: 20200250480
    Abstract: A training method, system, and computer program product include training a neural network including using two-sided ReLU as a non-linear function or norm-pooling as a non-linear function and increasing a confidence gap.
    Type: Application
    Filed: February 4, 2019
    Publication date: August 6, 2020
    Inventors: Haifeng Qian, Mark Wegman
  • Publication number: 20200250479
    Abstract: A training method, system, and computer program product include computing a matrix norm over a product of a weight matrix and a transpose of the weight matrix and using the matrix norm to constrain the L2 non-expansive neural network.
    Type: Application
    Filed: February 4, 2019
    Publication date: August 6, 2020
    Inventors: Haifeng Qian, Mark Wegman