公开(公告)号：US20250086425A1

公开(公告)日：2025-03-13

申请号：US18464056

申请日：2023-09-08

Applicant: NVIDIA Corporation

Inventor： Yunzhou Liu ,  Kyle Kranen ,  Mateusz Sieniawski ,  Mateusz Szczesny ,  Piotr Bigaj ,  Pawel Morkisz ,  Keval Morabia

IPC: G06N3/045

Abstract: Apparatuses, systems, and techniques to compare image generation quality of two or more image models. In at least one embodiment, a similarity metric that compares two or more images generated by the two or more image models from the same text description may be computed.

公开(公告)号：US20230418726A1

公开(公告)日：2023-12-28

申请号：US17850847

申请日：2022-06-27

Applicant: NVIDIA Corporation

Inventor： Szymon Migacz ,  Pawel Morkisz ,  Alex Fit-Florea ,  Maciej Bala ,  Jakub Zakrzewski ,  Trivikram Krishnamurthy ,  Nitin Nitin ,  Sangkug Lym ,  Shang Wang ,  Chenhan Yu ,  Alexandre Milesi

IPC: G06F11/36

CPC classification number: G06F11/3612

Abstract: Methods and systems for comparing information obtained during execution of a workload to a set of inefficiency patterns, and determining the workload includes a potential inefficiency when the information matches at least one of the set of inefficiency patterns.

公开(公告)号：US20250103868A1

公开(公告)日：2025-03-27

申请号：US18475872

申请日：2023-09-27

Applicant: NVIDIA Corporation

Inventor： Mateusz Sieniawski ,  Pawel Morkisz

IPC: G06N3/0475 ,  G06T5/00

Abstract: Apparatuses, systems, and techniques to generate an image using a neural network based model using a variable error threshold. In at least one embodiment, one or more neural networks are used to generate a final output image by iteratively removing noise from an initial image based, at least in part, on one or more variable error threshold values.

公开(公告)号：US20240119267A1

公开(公告)日：2024-04-11

申请号：US17950009

申请日：2022-09-21

Applicant: NVIDIA Corporation

Inventor： Slawomir Kierat ,  Piotr Karpinski ,  Mateusz Sieniawski ,  Pawel Morkisz ,  Szymon Migacz ,  Linnan Wang ,  Chen-Han Yu ,  Satish Salian ,  Ashwath Aithal ,  Alexandru Fit-Florea

IPC: G06N3/04 ,  G06N3/08

CPC classification number: G06N3/0481 ,  G06N3/08

Abstract: Apparatuses, systems, and techniques to selectively use one or more neural network layers. In at least one embodiment, one or more neural network layers are selectively used based on, for example, one or more iteratively increasing neural network performance metrics.