[Jan 30th 2019] Designing non-parametric activation functions: recent advances

Simone Scardapane and Aurelio Uncini (Università Sapienza) Jan 30, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Recently, the design of flexible nonlinearities has become an important line of research in the deep learning community. In the first part of the talk we will review how to tackle this problem, […]

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[Jan 23rd 2019] LabMeeting: Invertible conditional GANs

Lisa Graziani (DIISM, University of Siena) Jan 23, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Generative Adversarial Networks (GANs) allow to generate images and are used in a variety of applications, as image synthesis, semantic image editing, style transfer, image super-resolution, image transformation and classification. Relevant extensions of GANs […]

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[Jan 16th 2019] LabMeeting: Study of potential impact of copy number alterations of MAPK15 in High Grade Serous Ovarian Cancer

Giorgia Giacomini (DIISM, University of Siena) Jan 16, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description A powerful way to discover key genes playing causal roles in oncogenesis is to identify genomic regions that undergo frequent alteration in human cancers. Copy Number Alterations (CNAs) are structural rearrangements involving DNA segments, […]

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[Jan 9th 2019] LabMeeting: Automatic prediction of druggability for protein surface pockets

Pietro Bongini (DIISM, University of Siena) Jan 09, 2019 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Drug discovery is a flourishing field of research with the goal of improving human health. Even though, in the last two decades, a massive amount of informatics has been introduced in this field, providing […]

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[Dec 17th 2018] Deep Graph Infomax

Pietro Liò (University of Cambridge) Dec 17, 2018 – 2:30 PM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description We present Deep Graph Infomax (DGI), a general approach for learning node representations within graph-structured data in an unsupervised manner. DGI relies on maximizing mutual information between patch representations and corresponding high-level summaries of graphs—both […]

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[Dec 12th 2018] LabMeeting: How to extend GNNs: from changing the neuron model to transductive learning

Giorgio Ciano (DIISM, University of Siena) Dec 12, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Most of the techniques used in Machine Learning (e.g. Deep Neural Networks) use vectors as inputs. However, graphs are a data structure that is more general and suitable to represent real-world problems. Even if […]

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[Dec 12th 2018] Evolutionary Coresets and Machine Learning Epistemology

Pietro Barbiero (DISMA, Politecnico di Torino) Dec 12, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description In recent years, machine learning research has proposed effective algorithms, with huge impacts on applications ranging from medicine to autonomous driving cars. Although these models are powerful and accurate, they show serious weaknesses, such […]

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[Dec 12th 2018] Neural Biclustering in Gene Expression Analysis

Giansalvo Cirrincione (University of Picardie Jules Verne (UPJV), Amiens (France) and University of South Pacific (USP), Suva, Fiji) Dec 12, 2018 – 11:00 AM DIISM, Artificial Intelligence laboratory (room 201), Siena SI Description Clustering in high dimensional spaces is a very difficult task. Dealing with DNA microarrays is even more difficult because gene subsets are […]

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