公开(公告)号：US20240211549A1

公开(公告)日：2024-06-27

申请号：US18591640

申请日：2024-02-29

Applicant: Intel Corporation

Inventor： Marius Arvinte ,  Brandon Edwards ,  Cory Cornelius ,  Jason Martin ,  Sebastian Szyller ,  Micah Sheller ,  Nageen Himayat

IPC: G06F21/10

CPC classification number: G06F21/101

Abstract: An example apparatus includes interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access a first set of samples associated with a diffusion model, the first set of samples including a plurality of input data samples, generate a representation of the first set of samples, sample the representation of the first set of samples to generate a representation of a second set of samples, and generate the second set of samples from the representation of the second set of samples, the second set of samples including a plurality of output data samples, an output data sample corresponding to an input data sample and being different from the corresponding input data sample.

公开(公告)号：US11657162B2

公开(公告)日：2023-05-23

申请号：US16361397

申请日：2019-03-22

Applicant: Intel Corporation

Inventor： Michael Kounavis ,  Antonios Papadimitriou ,  Anindya Sankar Paul ,  Micah Sheller ,  Li Chen ,  Cory Cornelius ,  Brandon Edwards

IPC: G06F21/60 ,  G06N3/08 ,  G06N3/04 ,  G06F21/52

CPC classification number: G06F21/60 ,  G06F21/52 ,  G06N3/0454 ,  G06N3/08

Abstract: In one example an apparatus comprises a memory and a processor to create, from a first deep neural network (DNN) model, a first plurality of DNN models, generate a first set of adversarial examples that are misclassified by the first plurality of deep neural network (DNN) models, determine a first set of activation path differentials between the first plurality of adversarial examples, generate, from the first set of activation path differentials, at least one composite adversarial example which incorporates at least one intersecting critical path that is shared between at least two adversarial examples in the first set of adversarial examples, and use the at least one composite adversarial example to generate a set of inputs for a subsequent training iteration of the DNN model. Other examples may be described.

公开(公告)号：US20190220605A1

公开(公告)日：2019-07-18

申请号：US16361397

申请日：2019-03-22

Applicant: Intel Corporation

Inventor： Michael Kounavis ,  Antonios Papadimitriou ,  Anindya Paul ,  Micah Sheller ,  Li Chen ,  Cory Cornelius ,  Brandon Edwards

IPC: G06F21/60 ,  G06N3/04 ,  G06N3/08

CPC classification number: G06F21/60 ,  G06N3/0454 ,  G06N3/08

Abstract: In one example an apparatus comprises a memory and a processor to create, from a first deep neural network (DNN) model, a first plurality of DNN models, generate a first set of adversarial examples that are misclassified by the first plurality of deep neural network (DNN) models, determine a first set of activation path differentials between the first plurality of adversarial examples, generate, from the first set of activation path differentials, at least one composite adversarial example which incorporates at least one intersecting critical path that is shared between at least two adversarial examples in the first set of adversarial examples, and use the at least one composite adversarial example to generate a set of inputs for a subsequent training iteration of the DNN model. Other examples may be described.