Overall, the application of the Variational Autoencoder not only enhances the analytical capabilities of quantum simulations but also offers new perspectives for understanding the physical properties ...

In the last decade, auxiliary information has been widely used to address data sparsity. Due to the advantages of feature extraction and the no-label requirement, autoencoder-based methods addressing ...

Dr. James McCaffrey from Microsoft Research presents a complete program that uses the Python language LightGBM system to create a custom autoencoder for data anomaly detection. You can easily adapt ...

Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...

Penny Liang's book, "Understanding Large Models for Humanities Students (1.0)," explains the core technologies of large ...

Cintas, Celia, Skyler Speakman, Victor Akinwande, William Ogallo, Komminist Weldemariam, Srihari Sridharan, and Edward McFowland III. "Detecting Adversarial Attacks ...

Ziwei Zhu, Assistant Professor, Computer Science, College of Engineering and Computing (CEC), received funding for the project: “III: Small: Harnessing Interpretable Neuro-Symbolic Learning for ...

Sandia National Laboratories cybersecurity expert Adrian Chavez, left, and computer scientist Logan Blakely work to integrate ...

This technology is able to detect abnormalities in the grid and help us understand when we’re having a cyber attack or ...