In the field of international nuclear safeguards, the quantity of data that could support
verification of a state's peaceful nuclear energy program is growing at a rate which makes it …

Abstract Machine learning (ML) has seen many successes in a variety of domains from
image recognition to natural language processing. There has been a general call to apply …

Continued growth in the nuclear industry is resulting in an increased burden for regulators
due to the costs associated with implementing traditional safeguards. One such stakeholder …

International nuclear safeguards analysts use images in myriad ways to support verification
analysis tasks, from analyzing the design and construction of a facility to understanding the …

This study explores the mission space and key safeguards challenges confronting the
International Atomic Energy Agency (IAEA) today and how the status quo may be impacted …

Accurate and interpretable satellite health monitoring systems play a crucial role in keeping
a satellite operational. With potentially hundreds of sensors to monitor, identifying when and …

Hidden within our rapidly growing global streams of business, scientific, and
communications data, is information that can reduce the global danger of nuclear weapons …

Integrating machine learning (ML) into nuclear safety analysis has enhanced results quality,
but opaque ML algorithms pose trust challenges. Therefore, Explainability is crucial for …

Deep Neural Networks (DNNs) do not inherently compute or exhibit empirically-justified task
confidence. In mission critical applications, it is important to both understand associated …

In nuclear power plants (NPPs), anomalies arising from sensors or human errors (HEs) can
undermine the performance and reliability of plant operations. Anomaly detection models …