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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[Dec 7th 2022] LabMeeting: SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition

Simone Marullo When: Dec 7th, 2022 – 11:00 – 11:30 AM Where: Google meet link Description SIMONe: View-Invariant, Temporally-Abstracted Object Representations via Unsupervised Video Decomposition By Rishabh Kabra, Daniel Zoran, Goker Erdogan, Loic Matthey, Antonia Creswell Matthew Botvinick, Alexander Lerchner, Christopher P. Burgess To help agents reason about scenes in terms of their building blocks, […]

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[Nov 23th 2022] LabMeeting: Physics Informed Neural Networks for generation of structured grids on bounded domains

Giuseppe Alessio D’Inverno When: Nov 9th, 2022 – 11:00 – 11:30 AM Where: Google meet link Description Physics Informed Neural Networks for generation of structured grids on bounded domains The generation of structured grids on bounded domains is a crucial point in the development of numerical models for solving differential problems. In particular, the representation […]

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[Nov 9th 2022] LabMeeting: PARTIME: Scalable Multi-GPU Pipeline Parallelism

Enrico Meloni When: Nov 9th, 2022 – 11:30 – 12:00 AM Where: Google meet link Description PARTIME: Scalable Multi-GPU Pipeline Parallelism In this seminar, we present PARTIME, a software library written in Python and based on PyTorch, designed specifically to speed up neural networks whenever data is continuously streamed over time, for both learning and […]

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[Nov 9th 2022] LabMeeting: Drug Side Effect Prediction with Deep Learning Molecular Embedding in a Graph of Graphs Domain

Niccolò Pancino When: Nov 9th, 2022 – 11:00 – 11:30 AM Where: Google meet link Description Drug Side Effect Prediction with Deep Learning Molecular Embedding in a Graph of Graphs Domain In collaboration with Yohann Perronn, Pietro Bongini and Franco Scarselli Drug Side Effects (DSEs) or Adverse Drug Reactions (ADRs) constitute an important health risk, […]

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[Nov 2nd 2022] LabMeeting: Weighted simplicial complexes and their representation power of higher-order network data and topology

Federica Baccini When: Nov 2nd, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Weighted simplicial complexes and their representation power of higher-order network data and topology Hypergraphs and simplicial complexes both capture the higher-order interactions of complex systems, ranging from higher-order collaboration networks to brain networks. One open problem in the field […]

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[Oct 19th 2022] LabMeeting: TransformerFusion: Monocular RGB Scene Reconstruction using Transformers

Marco Tanfoni When: Oct 19th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Monocular RGB Scene Reconstruction using Transformers by A. Božič, P. Palafox, J. Thies, A. Dai, M. Nießner. We introduce TransformerFusion, a transformer-based 3D scene reconstruction approach. From an input monocular RGB video, the video frames are processed by a […]

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[Oct 12th 2022] LabMeeting: Lifelong Learning of Graph Neural Networks for Open-World Node Classification

Filippo Costanti When: Oct 12th, 2022 – 11:45 – 12:30 AM Where: Google meet link Description Lifelong Learning of Graph Neural Networks for Open-World Node Classification Graph neural networks (GNNs) have emerged as the standard method for numerous tasks on graph-structured data such as node classification. However, real-world graphs are often evolving over time and […]

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[Sep 28th 2022] LabMeeting: Continual Learning: an Optimal Control approach

Michele Casoni When: Sep 28th, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Continual Learning: an Optimal Control approach Continual Learning is a branch of Machine Learning which studies the ability of a model to learn continually from a stream of data. For academics and practitioners, this new way of conceiving learning […]

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[Sep 21st 2022] LabMeeting: Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging

Elia Giuseppe Ceroni When: Sep 21st, 2022 – 11:00 – 11:45 AM Where: Google meet link Description Deep learning for the prediction of early on-treatment response in metastatic colorectal cancer from serial medical imaging by Lin Lu, Laurent Dercle, Binsheng Zhao, and Lawrence H. Schwartz In current clinical practice, tumor response assessment is usually based […]

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