Paper on the capabilities of Deep Generative Learning accepted for presentation at HICSS-54
Algorithms that create previously unseen, yet realistic images and melodic music? Machine learning models that literally read human minds? Peter Hofmann, Timon Rückel and I shed light on the capabilities of Deep Generative Learning and are happy to present our paper "Innovating with Artificial Intelligence: Capturing the Constructive Functional Capabilities of Deep Generative Learning" at the 54th Hawaii International Conference on System Sciences (HICSS-54).
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