Introduction
Neural networks continue to grow in both size and complexity. Developing state-of-the-art architectures is often a cumbersome and time-consuming process that requires both domain expertise and large engineering efforts. In an attempt to overcome these challenges, several Neural Architecture Search (NAS) approaches have been proposed to automatically design well-performing architectures without requiring a human in-the-loop.