Apple researchers explore how AI can predict bugs, write tests, and even fix code

Apple has published three interesting studies that offer some insight into how AI can improve workflows, quality, and productivity for developers.

Apple's research explains how AI can identify bugs in code and generate QE tests

New papers on Apple's machine learning blog detail how AI can be used for faster, cheaper, and more effective QE testing, as ...
IEEE

Feature Guided Masked Autoencoder for Self-Supervised Learning in Remote Sensing

Abstract: Self-supervised learning guided by masked image modeling, such as masked autoencoder (MAE), has attracted wide attention for pretraining vision transformers in remote sensing. However, MAE ...
IEEE

Autoencoder Optimization for Anomaly Detection: A Comparative Study with Shallow Algorithms

Abstract: This paper presents an innovative guide for optimizing autoencoder performance, specifically targeting anomaly detection tasks. In addressing prevalent issues in deep learning algorithms, ...
C&EN

Soft Measurement Modeling Method Based on Quality-Related Mixed Variational Autoencoder Regression

Huzhou Key Laboratory of Intelligent Sensing and Optimal Control for Industrial Systems, School of Engineering, Huzhou University, Huzhou 313000, PR China Zhejiang Key Laboratory of Industrial Solid ...