PerturbNet is a generative AI model that can predict shifts in cell state—changes in overall gene expression—in response to ...

Classification of power system event data is a growing need, particularly where non-protective relaying-based sensors are used to monitor grid performance. Given the high burden of obtaining event ...

In semiconductor foundries, wafer map defect analysis is crucial to prevent yield excursion. However, traditional manual inspection can hardly meet the high-throughput demand. Deep learning-based ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

Experimental results demonstrate that autoencoder-like neural networks are suitable for unsupervised EEG modeling, and our proposed emotion recognition framework achieves an inspiring performance. As ...