Generative Adversarial Networks (GANs) have promoted a variety of applications in
computer vision and natural language processing, among others, due to its generative …

Generative deep learning algorithms have progressed to a point where it is difficult to tell the
difference between what is real and what is fake. In 2018, it was discovered how easy it is to …

Procedural content generation in video games has a long history. Existing procedural
content generation methods, such as search-based, solver-based, rule-based and grammar …

Generative Adversarial Networks (GANs) are a machine learning approach capable of
generating novel example outputs across a space of provided training examples. Procedural …

AI has provided us with the ability to automate tasks, extract information from vast amounts of
data, and synthesize media that is nearly indistinguishable from the real thing. However …

Learning to reject is a special kind of self-awareness (the ability to know what you do not
know), which is an essential factor for humans to become smarter. Although machine …

Quality diversity (QD) is a growing branch of stochastic optimization research that studies the
problem of generating an archive of solutions that maximize a given objective function but …

In the Internet-of-Things (IoT) era, user authentication is essential to ensure the security of
connected devices and the customization of passive services. However, conventional …

Procedural content generation (PCG) refers to the practice of generating game content, such
as levels, quests or characters, algorithmically. Motivated by the need to make games …

Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …