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Datasets and Benchmarks for Causal Learning
Csaba Szepesvari · Isabelle Guyon · Nicolai Meinshausen · David Blei · Elias Bareinboim · Bernhard Schölkopf · Pietro Perona

Fri Dec 07 12:30 PM -- 02:00 PM (PST) @

Author Information

Csaba Szepesvari (University of Alberta)
Isabelle Guyon (U. Paris-Saclay & ChaLearn)
Nicolai Meinshausen (ETH Zurich)
David Blei (Columbia University)

David Blei is a Professor of Statistics and Computer Science at Columbia University, and a member of the Columbia Data Science Institute. His research is in statistical machine learning, involving probabilistic topic models, Bayesian nonparametric methods, and approximate posterior inference algorithms for massive data. He works on a variety of applications, including text, images, music, social networks, user behavior, and scientific data. David has received several awards for his research, including a Sloan Fellowship (2010), Office of Naval Research Young Investigator Award (2011), Presidential Early Career Award for Scientists and Engineers (2011), Blavatnik Faculty Award (2013), and ACM-Infosys Foundation Award (2013). He is a fellow of the ACM.

Elias Bareinboim (Purdue)
Bernhard Schölkopf (MPI for Intelligent Systems)

Bernhard Scholkopf received degrees in mathematics (London) and physics (Tubingen), and a doctorate in computer science from the Technical University Berlin. He has researched at AT&T Bell Labs, at GMD FIRST, Berlin, at the Australian National University, Canberra, and at Microsoft Research Cambridge (UK). In 2001, he was appointed scientific member of the Max Planck Society and director at the MPI for Biological Cybernetics; in 2010 he founded the Max Planck Institute for Intelligent Systems. For further information, see www.kyb.tuebingen.mpg.de/~bs.

Pietro Perona (California Institute of Technology)

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