Abstract Design of structural and multidisciplinary systems under uncertainties requires
estimation of their reliability or equivalently the probability of failure under the given …

Studying extreme events and how they evolve in a changing climate is one of the most
important current scientific challenges. Starting from complex climate models, a key difficulty …

While autonomous vehicle (AV) technology has shown substantial progress, we still lack
tools for rigorous and scalable testing. Real-world testing, the $\textit {de-facto} $ evaluation …

We present a new approach to assessing the robustness of neural networks based on
estimating the proportion of inputs for which a property is violated. Specifically, we estimate …

Learning-based methodologies increasingly find applications in safety-critical domains like
autonomous driving and medical robotics. Due to the rare nature of dangerous events, real …

Adaptive multilevel splitting (AMS) is a rare event sampling method that requires minimal
parameter tuning and allows unbiased sampling of transition pathways of a given rare event …

Many turbulent flows undergo drastic and abrupt configuration changes with huge impacts.
As a paradigmatic example we study the multistability of jet dynamics in a barotropic beta …

The average time between two occurrences of the same event, referred to as its return time
(or return period), is a useful statistical concept for practical applications. For instance …

We introduce a generalization of the Adaptive Multilevel Splitting algorithm in the discrete
time dynamic setting, namely when it is applied to sample rare events associated with paths …

Rare events play a crucial role in many physics, chemistry, and biology phenomena, when
they change the structure of the system, for instance in the case of multistability, or when …