This paper proposes a complex recurrent variational autoencoder (VAE) framework, for modeling time series data, particularly speech signals. First, to account for the temporal structure of speech ...

We provide the pretrained models and also several images that reproduce the figures of the paper. Please download and unzip them here (2.1GB) (Note: this is a http ...

This library provides the capability to emulate MX-compatble formats and bfloat quantization in pytorch, enabling data science exploration for DNNs with different MX formats. The underlying ...

In this article, we propose a new contrastive conditional adversarial autoencoder for IOSFD. It constructs an end-to-end unified model based on multi-class known healthy and faulty data to address the ...