SAILab

Federica Baccini (University of Siena) When: Apr 14, 2021 – 11:00 – 11:45 AM Where: Google meet link Description We propose a method for gene expression based analysis of cancer phenotypes incorporating network biology knowledge through unsupervised construction of computational graphs. The structural construction of the computational graphs is driven by the use of topological […]

Gabriele Ciravegna (University of Siena) When: Mar 31, 2021 – 11:00 – 11:45 AM Where: Google meet link Description Despite the increasing popularity of deep learning application, in real wold domains the employment of deep neural networks is still limited and strongly criticized due to their lack of interpretability. In particular, providing a comprehensible explanation […]

Anna Visibelli (University of Siena) When: Mar 24, 2021 – 11:00 – 11:45 AM Where: Google meet link Description The plant Cannabis has been used for millennia for its medical and mind-altering effects. Clinical and preclinical research efforts over the past decades, have defined many effects of cannabis on physiology and behaviour and more recent […]

Luca Pasqualini (University of Siena) When: Mar 17, 2021 – 11:00 – 11:45 AM Where: Google meet link Description With the advent of 5G and the research into beyond 5G (B5G) networks, a novel and very relevant research issue is how to manage the coexistence of different types of traffic, each with very stringent but […]

Giorgio Ciano (University of Siena) When: Mar 10, 2021 – 11:00 – 11:45 AM Where: Google meet link Description Chest X-ray (CXR) is one of the most commonly used techniques for diagnosing pneumonia, tuberculosis, lung cancer, and heart failure. It is of great clinical and scientific interest to develop computer-based systems that support CXR analysis, […]

Enrico Meloni (University of Siena) When: Feb 10, 2021 – 11:00 – 11:45 AM Where: Google meet link Description Neural Models can be efficiently used for 2D and 3D reasoning. However, most 3D estimation models rely on supervised training, which comes with costly annotations of all observable 3D properties. Differentiable rendering enables 2D images to […]