公开(公告)号：US11410067B2

公开(公告)日：2022-08-09

申请号：US15753661

申请日：2016-08-18

Applicant: D-WAVE SYSTEMS INC.

Inventor： Jason Rolfe ,  Dmytro Korenkevych ,  Mani Ranjbar ,  Jack R. Raymond ,  William G. Macready

IPC: G06N10/00 ,  G06N20/00 ,  G06N3/08 ,  G06F15/80 ,  G06F17/18 ,  G06N5/04 ,  G06T1/20

Abstract: A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the digital processor can operate as a restricted Boltzmann machine. The computational system can operate as a quantum-based deep belief network operating on a training data-set.

公开(公告)号：US20210365826A1

公开(公告)日：2021-11-25

申请号：US17323143

申请日：2021-05-18

Applicant: D-WAVE SYSTEMS INC.

Inventor： Jason Rolfe ,  William G. Macready ,  Zhengbing Bian ,  Fabian A. Chudak

IPC: G06N10/00 ,  G06N3/04 ,  G06K9/00 ,  G06N3/08 ,  G06F15/80 ,  G06N20/00 ,  G06K9/62 ,  G06N20/10

Abstract: A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the computational system can perform unsupervised learning over an input space, for example via a discrete variational auto-encoder, and attempting to maximize the log-likelihood of an observed dataset. Maximizing the log-likelihood of the observed dataset can include generating a hierarchical approximating posterior. Unsupervised learning can include generating samples of a prior distribution using the quantum processor. Generating samples using the quantum processor can include forming chains of qubits and representing discrete variables by chains.

公开(公告)号：US11157817B2

公开(公告)日：2021-10-26

申请号：US15753666

申请日：2016-08-18

Applicant: D-Wave Systems Inc.

Inventor： Jason Rolfe

IPC: G06N10/00 ,  G06N3/08 ,  G06N3/04

Abstract: A computational system can include digital circuitry and analog circuitry, for instance a digital processor and a quantum processor. The quantum processor can operate as a sample generator providing samples. Samples can be employed by the digital processing in implementing various machine learning techniques. For example, the computational system can perform unsupervised learning over an input space, for example via a discrete variational auto-encoder, and attempting to maximize the log-likelihood of an observed dataset. Maximizing the log-likelihood of the observed dataset can include generating a hierarchical approximating posterior.

公开(公告)号：US11062227B2

公开(公告)日：2021-07-13

申请号：US15766755

申请日：2016-10-14

Applicant: D-WAVE SYSTEMS INC.

Inventor： Mohammad H. S. Amin ,  Evgeny Andriyash ,  Jason Rolfe

IPC: G06N10/00 ,  G06N20/00 ,  B82Y10/00 ,  G06N3/04

Abstract: A hybrid computer generates samples for machine learning. The hybrid computer includes a processor that implements a Boltzmann machine, e.g., a quantum Boltzmann machine, which returns equilibrium samples from eigenstates of a quantum Hamiltonian. Subsets of samples are provided to training and validations modules. Operation can include: receiving a training set; preparing a model described by an Ising Hamiltonian; initializing model parameters; segmenting the training set into subsets; creating a sample set by repeatedly drawing samples until the determined number of samples has been drawn; and updating the model. Operation can include partitioning the training set into input and output data sets, and determining a conditional probability distribution that describes a probability of observing an output vector given a selected input vector, e.g., determining a conditional probability by performing a number of operations to minimize an upper bound for a log-likelihood of the conditional probability distribution.

公开(公告)号：US20170116159A1

公开(公告)日：2017-04-27

申请号：US15399461

申请日：2017-01-05

Applicant: D-Wave Systems Inc.

Inventor： Firas Hamze ,  James King ,  Evgeny Andriyash ,  Catherine McGeoch ,  Jack Raymond ,  Jason Rolfe ,  William G. Macready ,  Aaron Lott ,  Murray C. Thom

IPC: G06F17/18 ,  G06N99/00

CPC classification number: G06F17/18 ,  G06N10/00 ,  G06N20/00

Abstract: The systems, devices, articles, and methods generally relate to sampling from an available probability distribution. The samples maybe used to create a desirable probability distribution, for instance for use in computing values used in computational techniques including: Importance Sampling and Markov chain Monte Carlo systems. An analog processor may operate as a sample generator, for example by: programming the analog processor with a configuration of the number of programmable parameters for the analog processor, which corresponds to a probability distribution over qubits of the analog processor, evolving the analog processor, and reading out states for the qubits. The states for the qubits in the plurality of qubits correspond to a sample from the probability distribution. Operation of the sampling device may be summarized as including updating a set of samples to include the sample from the probability distribution, and returning the set of samples.