[Jun 26th 2019] LabMeeting: Convolutional Networks with Adaptive Inference Graphs

Pietro Bongini (DIISM, University of Siena) Jun 26, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Do convolutional networks really need a fixed feed-forward structure? What if, after identifying the high-level concept of an image, a network could move directly to a layer that can distinguish fine-grained differences? Currently, a […]

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LYRICS: integrating Logic and Deep Learning

LINK TO THE PAPER https://arxiv.org/abs/1903.07534 LINK TO THE REPO https://github.com/GiuseppeMarra/lyrics In spite of the amazing results obtained by deep learning in many applications, a real intelligent behavior of an agent acting in a complex environment is likely to require some kind of higher-level symbolic inference. Therefore, there is a clear need for the definition of a […]

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[Jun 12th 2019] LabMeeting: Neural Markov logic networks

Giuseppe Marra (DIISM, University of Florence and Siena) Jun 12, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Markov Logic Networks (MLN) are a very well-known example of statistical relational model. In order to build good models, MLNs ask the user to define in advance a set of first-order logic […]

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The Graph Neural Network framework

LINK https://sailab.diism.unisi.it/gnn/ Our research group introduced the Graph Neural Network (GNN), a connectionist model particularly suited for problems whose domain can be represented by a set of patterns and relationships between them. In those problems, a prediction about a given pattern can be carried out exploiting all the related information, which includes the pattern features, […]

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