Recent work has shown great promise in explaining neural network behavior. In particular,
feature attribution methods explain the features that are important to a model's prediction on …

Deep learning methods have emerged as powerful tools for analyzing histopathological
images, but current methods are often specialized for specific domains and software …

The era of pervasive computing has resulted in countless devices that continuously monitor
users and their environment, generating an abundance of user behavioural data. Such data …

Featured Application Using Neuroscope to evaluate CNNs for semantic segmentation of
traffic scenes for autonomous driving. Abstract Trust in artificial intelligence (AI) predictions is …

Artificial intelligence shows promise for solving many practical societal problems in areas
such as healthcare and transportation. However, the current mechanisms for AI model …

In recent years, there has been an increasing trend of applying artificial intelligence in many
different fields, which has a profound and direct impact on human life. Consequently, this …

Social media plays a significant role in sharing essential information, which helps
humanitarian organizations in rescue operations during and after disaster incidents …

This thesis touches upon two main topics: interpreting machine learning models, and the
application of machine learning to protein sequences and structures. The first portion deals …

Visualization methods can assist in the interpretation of deep neural networks. Recent years
have witnessed many advances in visualization and saliency methods. But all the methods …

As complex, black box models have increasingly come to predominate the algorithms used
in state-of-the-art machine learning pipelines, the need to explain and understand the …