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Introduction.- Fundamentals of Statistical Inference.- Model-Based Machine Learning and Approximate Inference.- Bayesian Neural Networks.- Variational Autoencoders.- Conclusion.
Lucas P. Cinelli was born in Rio de Janeiro, Brazil. He received the Electronics and Computer Engineering degree from the Universidade Federal do Rio de Janeiro (UFRJ), as well as the Engineering degree with major in Electronic Systems, Networks & Images from the Grande École Supélec, in France, due to his academic exchange in 2014-2016. During this period, he also received the Master’s degree in Microtechnologies, Architecture, Communication Networks and Systems from Supélec/INSA-Rennes. In 2019, he received the M.Sc. degree in Electrical Engineering from COPPE/UFRJ, for his dissertation on variational methods for machine learning and is currently pursuing his Ph.D. degree at the same institution. His research on anomaly detection in videos with deep learning alongside his colleagues has led to publications on ICIP 2018 and a Brazilian conference (SBrT) in 2017.
Matheus A. Marins was born in Rio de Janeiro, Brazil. He received the Electronics and Computer Engineering degree from the Universidade Federal do Rio de Janeiro (UFRJ), in 2016, having done a one-year exchange program at Illinois Institute of Technology (IIT), in the Computer Engineering course. He received the M.Sc. degree in Electrical Engineering from COPPE/UFRJ in 2018, being awarded with a scholarship for his academic performance by the Rio de Janeiro State government. Currently, he is pursuing his Ph.D. degree at the same institution and has shifted his research towards modern Bayesian methods applied to Machine Learning. So far, his research has been focused on Machine Learning, especially on condition-based models to identify and prevent failures on physical systems, which resulted on two international journals (2017 and 2020) and on a Brazilian conference paper (SBrT).Sergio L. Netto was born in Rio de Janeiro, Brazil. He received the B.Sc. (cum laude) degree from the Universidade Federal do Rio de Janeiro (UFRJ), Brazil, in 1991, the M.Sc. degree from COPPE/UFRJ in 1992, and the Ph.D. degree from the University of Victoria, BC, Canada, in 1996, all in electrical engineering. Since 1997, he has been with the Department of Electronics and Computer Engineering, Poli/UFRJ, and since 1998, he has been with the Program of Electrical Engineering, COPPE/UFRJ. He is the Co-Author (with P. S. R. Diniz and E. A. B. da Silva) of Digital Signal Processing: System Analysis and Design (Cambridge University Press, 2nd edition, 2010), which has also been translated to Chinese and Portuguese. His research and teaching interests lie in the areas of digital signal processing,speech processing, information theory, and computer vision. Prof. Netto received the 2006 Guillemin-Cauer award from the IEEE Circuits and Systems Society for the best paper published in the year of 2005 in the IEEE Trans. Circuits and Systems, Part I: Regular Papers.
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