One fundamental goal of cognitive science is to understand how humans mentally represent concepts. One approach to this is to survey humans how they perceive objects and their similarity.
One fundamental goal of cognitive science is to understand how humans mentally represent concepts. One approach to this is to survey humans how they perceive objects and their similarity. The first part of this talk will cover VICE, a Bayesian method for inferring geometric representations of concepts, i.e. vector embeddings, whose geometry is consistent with similarity task responses. Representations from VICE are very effective at predicting human responses to object similarity tasks. Representation dimensions from VICE are highly interpretable, thus revealing what properties are important when humans consider object similarity.
The second part of this talk will investigate how these human representations compare to neural network representations on the THINGS dataset, a collection of 1,854 object categories carefully curated for cognitive science research. Here we see what kinds of networks are best aligned to human understanding and what object properties that humans find important are also understood by neural networks.
Dr. Robert A. Vandermeulen received his PhD in Electrical Engineering from the University of Michigan in 2016. He was a postdoctoral researcher under Prof. Dr. Marius Kloft at Technical University Kaiserslautern from 2017 to 2020 and is currently a senior researcher at the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Dr. Vandermeulen's work spans many topics, however his most prominent work concerns deep anomaly detection where his work on deep one-class classification was awarded the SIGKDD Workshop on Anomaly and Novelty Detection, Explanation and Accommodation Test of Time Award.
Its program consists of a one-hour lecture followed by a discussion. The lecture is based on an (internationally) exceptional or remarkable achievement of the lecturer, presented in a way which is comprehensible and interesting to a broad computer science community. The lectures are in English.
The seminar is organized by the organizational committee consisting of Roman Barták (Charles University, Faculty of Mathematics and Physics), Jaroslav Hlinka (Czech Academy of Sciences, Computer Science Institute), Michal Chytil, Pavel Kordík (CTU in Prague, Faculty of Information Technologies), Michal Koucký (Charles University, Faculty of Mathematics and Physics), Jan Kybic (CTU in Prague, Faculty of Electrical Engineering), Michal Pěchouček (CTU in Prague, Faculty of Electrical Engineering), Jiří Sgall (Charles University, Faculty of Mathematics and Physics), Vojtěch Svátek (University of Economics, Faculty of Informatics and Statistics), Michal Šorel (Czech Academy of Sciences, Institute of Information Theory and Automation), Tomáš Werner (CTU in Prague, Faculty of Electrical Engineering), and Filip Železný (CTU in Prague, Faculty of Electrical Engineering)
The idea to organize this seminar emerged in discussions of the representatives of several research institutes on how to avoid the undesired fragmentation of the Czech computer science community.
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