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 ...

In the new wave of digital transformation, Guangxi Power Grid Co., Ltd. has recently applied for a patent titled "An Intelligent Generation Method and System for API Data Stream Security Labels," with ...

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 ...

Accurate measurement of time-varying systematic risk exposures is essential for robust financial risk management.

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 ...

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 ...

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