Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …

Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …

Humans are able to recognize structured relations in observation, allowing us to decompose
complex scenes into simpler parts and abstract the visual world in multiple levels. However …

A central goal of artificial intelligence in high-stakes decision-making applications is to
design a single algorithm that simultaneously expresses generalizability by learning …

With the growing success of neural networks, there is a corresponding need to be able to
explain their decisions—including building confidence about how they will behave in the …

Deep learning has recently seen rapid development and received significant attention due
to its state-of-the-art performance on previously-thought hard problems. However, because …

Deep learning's great success motivates many practitioners and students to learn about this
exciting technology. However, it is often challenging for beginners to take their first step due …

We propose a framework for interactive and explainable machine learning that enables
users to (1) understand machine learning models;(2) diagnose model limitations using …

Deep neural networks have reached human-level performance on many computer vision
tasks. However, the objectives used to train these networks enforce only that similar images …

Deep learning is increasingly used in decision-making tasks. However, understanding how
neural networks produce final predictions remains a fundamental challenge. Existing work …