Welcome!

This is the official web site of Siena Artificial Intelligence Laboratory. The focus of our research is on machine learning. In the last few years, we’ve been mainly involved in the conception of new theories of learning in structured domains and in their applications to pattern recognition and mining the web. We are also interested […]

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[Jul 22nd 2020] LabMeeting: Partial Distance Correlation for Exploring Dependence Between Similarity Networks

Federica Baccini (University of Florence) Jul 22, 2020 – 11:00 AM Conference Meeting Description Similarity network fusion is a tool that aggregates the information coming from a multiplex network into a unique layer through a cross diffusion process. However, the process itself does not allow to infer which layer has the major impact in the […]

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[Jul 15th 2020] LabMeeting: Can Domain Knowledge Alleviate Adversarial Attacks in Multi-Label Classifiers?

Gabriele Ciravegna (University of Florence) Jul 15, 2020 – 11:00 AM Conference Meeting Description Adversarial attacks on machine learning-based classifiers, along with defence mechanisms, have been widely studied in the context of single-label classification problems. In this paper, we shift the attention to multi-label classification, where the availability of domain knowledge on the relationships among […]

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SAILenv

SAILenv is a Virtual Environment powered by Unity3D. It includes 3 pre-built scenes with full pixel-wise annotations. SAILenv is capable of generating frames at real-time speed, complete with pixel-wise annotations, optical flow and depth. SAILenv also comes with a Python API, designed to easily integrate with the most common learning frameworks available. Pixel-wise Annotations SAILenv […]

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[July 1st 2020] LabMeeting: Next Segment Prediction

Lisa Graziani (University of Florence) Jul 1, 2020 – 11:00 AM Conference Meeting Description In general sketches are generated using generative adversarial models. We propose a new approach which represents the sketches as sequences of segments. This means that segments are ordered with respect to time, so we organize them considering a predefi ned criterion. We […]

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[Jun 24th 2020] LabMeeting: mCSM-membrane: predicting the effects of mutations on transmembrane proteins

Anna Visibelli (University of Siena) Jun 24, 2020 – 11:00 AM Conference Meeting Description Significant efforts have been invested into understanding and predicting the molecular consequences of mutations in protein coding regions, however nearly all approaches have been developed using globular, soluble proteins. These methods have been shown to poorly translate to studying the effects […]

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Towards Laws of Visual Attention

PH.D. THESIS Author: Dario Zanca Date: March, 2019 Topics: Computational modeling of visual attention; Computer vision; Machine Learning. Abstract Visual attention is a crucial process for humans and foveated animals in general. The ability to select relevant locations in the visual field greatly simplifies the problem of vision. It allows a parsimonious management of the […]

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[Jun 17th 2020] LabMeeting: Analyzing and Improving the Image Quality of StyleGAN

Giorgio Ciano (University of Florence) Jun 17, 2020 – 11:00 AM Conference Meeting Description The style-based GAN architecture (StyleGAN) yields state-of-the-art results in data-driven unconditional generative image modeling. We expose and analyze several of its characteristic artifacts, and propose changes in both model architecture and training methods to address them. In particular, we redesign generator […]

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[Jun 3rd 2020] LabMeeting: Wave Propagation of Visual Stimuli in Focus of Attention

Lapo Faggi (University of Florence) Jun 3, 2020 – 11:00 AM Conference Meeting Description Fast reactions to changes in the surrounding visual environment require efficient attention mechanisms to reallocate computational resources to the most relevant locations in the visual field. While current computational models keep improving their predictive ability thanks to the increasing availability of […]

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[May 20th 2020] LabMeeting: Towards understanding glasses with graph neural networks

Niccolò Pancino May 20, 2020 – 11:00 AM Conference Meeting Description The glass transition is a reversible transition that occurs when an amorphous polymer material is heated or cooled in a particular temperature range. On cooling, the material becomes less flexible, like a glass, and on heating becomes soft. This characteristics dramatically affects the usefulness […]

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