Big graduation day in the ML family with 3 newly graduated students (two cum laude!) on topics ranging from neuro-probabilistic models for graphs, interpretability of graph neural networks for chemistry and cognitive architectures for creativity. Congratulations!
Daniele Arioli, CognAC: a cognitive architecture based on Information Dynamics of Thinking, co-supervised with V. Gervasi, M.Sc. in Computer Science & Artificial Intelligence
Valerio De Caro, Graph Relative Density Networks, M.Sc. in Computer Science & Artificial Intelligence
Danilo Numeroso, Explaining Deep Graph Networks By Structured Counterfactual Explanations, M.Sc. in Computer Science & Artificial Intelligence