In recent years, Deep Reinforcement Learning (DRL) has become a popular paradigm in
machine learning due to its successful applications to real-world and complex systems …

Deep Neural Networks (DNNs) are powerful tools that have shown extraordinary results in
many scenarios, ranging from pattern recognition to complex robotic problems. However …

In recent years, Deep Reinforcement Learning (DRL) has emerged as an effective approach
to solving real-world tasks. However, despite their successes, DRL-based policies suffer …

Deep Neural Networks (DNN) are crucial in approximating nonlinear functions across
diverse applications, ranging from image classification to control. Verifying specific input …

Probabilistic verification of neural networks is concerned with formally analysing the output
distribution of a neural network under a probability distribution of the inputs. Examples of …

We study the problem of assessing the robustness of counterfactual explanations for deep
learning models. We focus on $\textit {plausible model shifts} $ altering model parameters …