Antonio Vergari (Preferred)
, antonio vergari
Antonio Vergari
University of Edinburgh
Names
How do you usually write your name as author of a paper? Also add any other names you have authored papers under.
Emails
Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. This information is crucial for deduplicating users, and ensuring you see your reviewing assignments.
****@aim.com
, ****@tuebingen.mpg.de
, ****@uniba.it
, ****@cs.ucla.edu
, ****@ed.ac.uk
, ****@exseed.ed.ac.uk
Personal Links
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Education & Career History
Enter your education and career history. The institution domain is used for conflict of interest detection and institution ranking. For ongoing positions, leave the end field blank.
Lecturer
University of Edinburgh (ed.ac.uk)
2021 – Present
Postdoc
University of California, Los Angeles (ucla.edu)
2019 – 2021
Postdoc
Max-Planck Institute (mpg.de)
2018 – 2019
Postdoc
Max-Planck-Insitute for Intelligent Systems (tuebingen.mpg.de)
2018 – 2019
PhD student
University of Bari (uniba.it)
2015 – 2018
PhD student
Università degli Studi di Bari (uniba.it)
2015 – 2018
Advisors, Relations & Conflicts
Enter all advisors, co-workers, and other people that should be included when detecting conflicts of interest.
Coworker
Robert Peharz
****@tue.nl
2017 – Present
Postdoc Advisor
Guy Van den Broeck
****@cs.ucla.edu
2019 – 2021
Coworker
Daniel Lowd
****@cs.uoregon.edu
2019 – 2019
Coworker
Tahrima Rahman
****@utdallas.edu
2019 – 2019
Postdoc Advisor
Isabel Valera
****@tuebingen.mpg.de
2018 – 2019
Coworker
Tameem Adel
****@cam.ac.uk
2018 – 2019
PhD Advisor
Kristian Kersting
****@cs.tu-darmstadt.de
2017 – 2018
PhD Advisor
Floriana Esposito
****@uniba.it
2015 – 2018
PhD Advisor
Nicola Di Mauro
****@uniba.it
2015 – 2018
Expertise
For each line, enter comma-separated keyphrases representing an intersection of your interests. Think of each line as a query for papers in which you would have expertise and interest. For example: deep learning, RNNs, dependency parsing
Neuro-symbolic reasoning
2020 – Present
Anomaly Detection
2017 – Present
Deep Learning
2016 – Present
Representation Learning
2016 – Present
Multi-label Classification
2016 – Present
Probabilistic Learning
2015 – Present
Machine Learning, Probabilistic Graphical Models, Representation Learning
2015 – Present
Machine Learning
2014 – Present
Probabilistic Graphical Models
2014 – Present
Tractable Probabilistic Models
2014 – Present
Exact Inference
2014 – Present