easchaw/Interpretable-Autoencoder-based-Neural-Networks

Deep Neural Networks achieve the state-of-the-art performance, this is not enough. They lack the ability to bring intuitiveness to the end user in terms of explaining the output of the model. The novel architectures proposed in this research will address vulnerabilities in the domain and hence will provide insights for the end users.