IEEE

ViGLAD: Vision Graph Neural Networks for Logical Anomaly Detection

Abstract: Quality inspection is an industrial field with a growing interest in anomaly detection research. An anomaly in an image can either be structural or logical. While structural anomalies lie on ...
Scientific Research Publishing

Hamilton, W., Ying, Z. and Leskovec, J. (2017) Inductive Representation Learning on Large Graphs. 31st Conference on Neural Information Processing Systems (NIPS 2017), Long ...

ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...
Ars Technica

Qubit that makes most errors obvious now available to customers

We’re nearing the end of the year, and there are typically a flood of announcements regarding quantum computers around now, in part because some companies want to live up to promised schedules. Most ...
SecurityWeek

ShadowLogic Attack Targets AI Model Graphs to Create Codeless Backdoors

Manipulation of an AI model’s graph can be used to implant codeless, persistent backdoors in ML models, AI security firm HiddenLayer reports. Dubbed ShadowLogic, the technique relies on manipulating a ...
IEEE

Transferable Presynthesis PPA Estimation for RTL Designs With Data Augmentation Techniques

Abstract: In modern VLSI design flow, evaluating the quality of register-transfer level (RTL) designs involves time-consuming logic synthesis using electronic design automation tools, a process that ...