Uploaded by AUTH Tropical (a.k.a. max-plus) algebra has been developed in the 1980’s and has been applied successfully in nonlinear image processing, control and optimization. Tropical geometry is a relatively recent field in mathematics and computer science combining elements of algebraic geometry and polyhedral geometry. The scalar arithmetic of its analytic part pre-existed in the… Continue reading https://icarus.csd.auth.gr/tropical-algebra-and-geometry-for-machine-learning-and-optimization-2/
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Geometric Learning: Foundations and Applications
Uploaded by AUTH Geometric Learning developed as a specific field of research that aims to learn from non-Euclidean domains, like graphs, manifolds, etc. In this tutorial, we first introduce the basic theory and challenges related to learning from these data, presenting basic architectural solutions for graphs, point clouds, and meshes. Then, we will present some… Continue reading Geometric Learning: Foundations and Applications
Generative AI for Animating 3D Human Face and Body Behaviors
Uploaded by AUTH Human behavior, both for face (e.g., expressions) and body (e.g., actions) has been studied in detail (for example for expression / action classification and prediction), but there have been few works exploring generation of novel behaviors. Generating novel sequences of human facial expression, talking heads, or body to form a natural and… Continue reading Generative AI for Animating 3D Human Face and Body Behaviors
Introduction to Artificial Social Intelligence
Uploaded by AUTH The tutorial is an introduction to the main aspects of Artificial Social Intelligence (Social AI), the AI domain aimed at making machines socially intelligent, i.e., capable to make sense of the social landscape in the same way as people do. The focus will be on the most specific aspects of the field… Continue reading Introduction to Artificial Social Intelligence
Quantitatively Assessing Explainable AI for Deep Neural Networks – a Crash Course
Uploaded by AUTH Deep Neural Networks (DNNs) are increasingly pervasive into society, especially in decision-making, in applications involving humans or in high-stake applications. This prompts the need for transparency, which is one of the cornerstones of the EU guidelines for Trustworthy AI. For DNNs, it is often unfeasible to attain human-understandable interpretations of the predictive… Continue reading Quantitatively Assessing Explainable AI for Deep Neural Networks – a Crash Course
On the possible outputs of human brains and intelligent machines
Uploaded by AUTH In this presentation I will argue that present-day intelligent machines, featuring the presently available modes of input and of input analysis procedures, cannot possibly produce identical outputs with those of human brains. The latter produce discriminant responses or publicly accessible behavior, more generally, on the one hand and subjective conscious experiences, on… Continue reading On the possible outputs of human brains and intelligent machines