Despite its great success, machine learning can have its limits when dealing with insufficient
training data. A potential solution is the additional integration of prior knowledge into the …

Despite the sudden rise of AI, it still leaves a question mark to many newcomers on its
widespread adoption as it exhibits a lack of robustness and interpretability. For instance, the …

The emergence of ground-breaking technologies such as artificial intelligence, cloud
computing, big data powered by the Internet, and its highly valued real-world applications …

In this study, we designed a four-dimensional (4D) audiovisual entertainment system called
Sense. This system comprises a scene recognition system and hardware modules that …

Symmetry detection can improve various machine learning tasks. In the context of
continuous symmetry detection, current state of the art experiments are limited to detecting …

The incorporation of prior knowledge into the ma-chine learning pipeline is subject of
informed machine learning. Spatial invariances constitute a class of prior knowledge that …

We propose a novel framework to design Ambisonic signal processing deep neural
networks (DNNs) that guarantee physical symmetries. In general, spatial acoustic signal …

In the last decades, Artificial Intelligence has witnessed multiple breakthroughs in deep
learning. In particular, purely data-driven approaches have opened to a wide variety of …

To replace data augmentation, this paper proposed a method called SLAP to intensify
experience to speed up machine learning and reduce the sample size. SLAP is a model …

The state of artificial intelligence technology has a rich history that dates back decades and
includes two fall-outs before the explosive resurgence of today, which is credited largely to …