A convolutional neural network-based classifier is elaborated to retrace the initial orientation
of deformed nucleus-nucleus collisions by integrating multiple typical experimental …

Polyhedral geometry can be used to shed light on the behaviour of piecewise linear neural
networks, such as ReLU-based architectures. Counterfactual explanations are a popular …

Deep neural networks (DNNs) are increasingly being deployed to perform safety-critical
tasks. The opacity of DNNs, which prevents humans from reasoning about them, presents …

Enhancing the synergy between autonomous and human-driven vehicles at the societal
level requires understanding drivers' behaviors and cognitive patterns, as well as …

The transformer neural network has significantly out-shined all other neural network
architectures as the engine behind large language models. We provide a theoretical …

Large language models encode the correlational structure present in natural language by
fitting segments of utterances (tokens) into a high dimensional ambient latent space upon …

Addressing the imperative need for efficient artificial intelligence in IoT and edge computing,
this study presents RepAct, a re-parameterizable adaptive activation function tailored for …

It's hard to express the extent to which deep neural networks have transformed machine
learning. Networks continue to get larger and more complex and find wider and wider …

This article addresses the influence of political correctness on the Chinese game Black
Myth: Wukong, particularly through the lens of feminist criticism. Using Natural Language …