[HTML][HTML] A systematic review of synthetic data generation techniques using generative AI

M Goyal, QH Mahmoud - Electronics, 2024‏ - mdpi.com
Synthetic data are increasingly being recognized for their potential to address serious real-
world challenges in various domains. They provide innovative solutions to combat the data …

Artificial intelligence approaches for energetic materials by design: state of the art, challenges, and future directions

JB Choi, PCH Nguyen, O Sen… - Propellants …, 2023‏ - Wiley Online Library
Artificial intelligence (AI) is rapidly emerging as a enabling tool for solving complex materials
design problems. This paper aims to review recent advances in AI‐driven materials‐by …

Unsupervised deep subgraph anomaly detection

Z Zhang, L Zhao - 2022 IEEE International Conference on Data …, 2022‏ - ieeexplore.ieee.org
Effectively mining anomalous subgraphs in networks is crucial for many application
scenarios, such as disease outbreak detection, financial fraud detection, and activity …

Deep generative model for periodic graphs

S Wang, X Guo, L Zhao - Advances in Neural Information …, 2022‏ - proceedings.neurips.cc
Periodic graphs are graphs consisting of repetitive local structures, such as crystal nets and
polygon mesh. Their generative modeling has great potential in real-world applications such …