Networks seminar low-dimensions representations of networks: March 28th
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Liubov
Mar 18, 2024, 3:01:13 AM3/18/24
to network-se...@googlegroups.com, rndapprendre
Dear all,
Really happy to invite you for the network seminar, which is going to be on the 28th March at 3pm CET (please mind the unusual time!) online.
We are really excited to have
Jean-Gabriel Young, Assistant Professor of Mathematics and
Statistics at The University of Vermont, VT, USA and who is
co-directing
the joint lab.
Register to get a link at:
Talk title: What can we learn from low-dimensions representations of networks?
Abstract: Machine learning systems now routinely use embeddings in thousands of dimensions to extract patterns from large-scale network data. Should we embrace this data revolution and let go of simpler network theories---S1 models, Bradley-Terry models, and so on?
In this talk, I will argue that low-dimensional embedding can reveal powerful yet interpretable network patterns and thus have a place in any modern data science stack.
I will illustrate this point through a number of stories about social hierarchies and decision-making.
Bio: Jean-Gabriel Young is an Assistant Professor of Mathematics and Statistics at The University of Vermont, VT, USA, where he co-directs the joint lab. His research focuses on the intersection of statistical inference, epidemiology, and complex systems. Previously, he was a James S. McDonnell Foundation Fellow at the Center for the Study of Complex Systems at the University of Michigan, mentored by Prof. Mark Newman. He obtained his PhD in Physics from Université Laval, under the guidance of Prof. Louis J. Dubé and Prof. Patrick Desrosiers.
Abstract: Machine learning systems now routinely use embeddings in thousands of dimensions to extract patterns from large-scale network data. Should we embrace this data revolution and let go of simpler network theories---S1 models, Bradley-Terry models, and so on?
In this talk, I will argue that low-dimensional embedding can reveal powerful yet interpretable network patterns and thus have a place in any modern data science stack.
I will illustrate this point through a number of stories about social hierarchies and decision-making.
Bio: Jean-Gabriel Young is an Assistant Professor of Mathematics and Statistics at The University of Vermont, VT, USA, where he co-directs the joint lab. His research focuses on the intersection of statistical inference, epidemiology, and complex systems. Previously, he was a James S. McDonnell Foundation Fellow at the Center for the Study of Complex Systems at the University of Michigan, mentored by Prof. Mark Newman. He obtained his PhD in Physics from Université Laval, under the guidance of Prof. Louis J. Dubé and Prof. Patrick Desrosiers.
On behalf of the network seminar organizers.
Bests,
Liubov
Research projects
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Our recent papers published:
Charting knowledge space mobility, EPJ 2024
Quantifying rise and fall of the scientific field, Plos One, 2023
Join our Network seminar mailing list!
Charting knowledge space mobility, EPJ 2024
Quantifying rise and fall of the scientific field, Plos One, 2023
Join our Network seminar mailing list!
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