HeKKSaGOn AI Symposium

Contribution List

11. Robotics and AI - Overview from Robotics Point of View

Kazuhiro Kosuge (Tohoku University / The University of Hong Kong)

9/19/23, 10:00 AM

Joint Session

Keynotes

Robotics and AI are often thought of as science. The Robotics Society of Japan is "Nippon Robotto Gakkai" in Japanese. "Nippon" means "Japan", "Robotto" means "robot", and "Gakkai" is the combination of two words, "Gaku" and "Kai". "Kai" means "society" in English, but "Gaku" is neither "science" nor "technology". "Gaku" means disciplines related to the field. "Robotto Gaku" means disciplines...

9. Non-classically generalized complex numbers

Wolf-Dieter Richter (University of Rostock, Institute of Mathematics)

9/19/23, 11:30 AM

Joint Session

Keynotes

The generalizations of complex numbers considered here differ from well-known generalizations such as quaternions, octonions, bicomplex and multicomplex numbers and Clifford algebras, to name some of the well-known ones, in at least two fundamental respects.

First of all, products of elements of such traditional algebraic structures are explained by the fact that certain expressions in...

23. Sticky Flavors in the Space of Phylogenetic Trees

Lars Lammers (Georg-August Universität Göttingen)

9/19/23, 2:45 PM

Joint Session

Plenary

Statistical inference in the field of phylogenetics requires the adaptiion of many classical methods to more general metric frameworks. The Fréchet-mean of a probability distribution is a generalisation of the expectation to metric spaces. It has been observed that the sample mean of certain probability distributions in Billera-Holmes-Vogtmann (BHV) phylogenetic spaces is confined to a...

22. AI Alignment / Safety

Georgios Kaklamanos (GWDG)

9/20/23, 9:45 AM

Joint Session

Keynotes

In recent months, there has been an increasing discussion about the advances of AI Technologies and their potential effects on society, particularly the negative ones.

In this talk, we will start with an overview of the current field of AI Safety and present the most prominent research agendas. Then, we will move on to interpretability research, specifically focusing on "Discovering Latent...

25. A Measure of the Complexity of Neural Representations based on Partial Information Decomposition

David Alexander Ehrlich (Campus Institute for Dynamics of Biological Networks)

9/20/23, 2:45 PM

Joint Session

Plenary

Despite their widespread adoption, the inner workings of Deep Neural Networks (DNNs) remain largely unknown. One key aspect of DNN learning is how the hidden layers' activation patterns encode the ground-truth label that the network is supposed to predict. This task-relevant information is represented jointly by groups of neurons within a layer. However, the specific way in which this mutual...