Abstract Generative Artificial Intelligence (GAI) is attracting the increasing attention of
materials community for its excellent capability of generating required contents. With the …

In agricultural image analysis, optimal model performance is keenly pursued for better
fulfilling visual recognition tasks (eg, image classification, segmentation, object detection …

Denoising diffusion probabilistic models are becoming the leading generative modeling
paradigm for many important data modalities. Being the most prevalent in the computer …

Heterogeneous tabular data are the most commonly used form of data and are essential for
numerous critical and computationally demanding applications. On homogeneous datasets …

Generative artificial intelligence (AI) has emerged as a powerful technology with numerous
applications in various domains. There is a need to identify the requirements and evaluation …

We propose a novel high-performance and interpretable canonical deep tabular data
learning architecture, TabNet. TabNet uses sequential attention to choose which features to …

Synthetic data consists of artificially generated data. When data are scarce, or of poor
quality, synthetic data can be used, for example, to improve the performance of machine …

This explainer document aims to provide an overview of the current state of the rapidly
expanding work on synthetic data technologies, with a particular focus on privacy. The …

Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …

This paper presents an AI-guided approach to automatically discover low-carbon cost-
effective ultra-high performance concrete (UHPC). The presented approach automates data …