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Causality Workbench
Isabelle Guyon

Tue Dec 08 12:00 AM -- 12:00 AM (PST) @
Event URL: http://www.causality.inf.ethz.ch/credits.php »

We will demonstrate the Causality Workbench, which is a web portal to aid research on causality. The Causality Workbench has served to community since 2007. The central novel piece of the workbench is the virtual laboratory
http://www.causality.inf.ethz.ch/workbench.php. The virtual laboratory allows researchers on causality to perform experiments on artificial systems in order to unravel causal relationships. The problem of attributing causes to effects is pervasive in science, medicine, economy and almost every aspects of our everyday life involving human reasoning and decision making. One important goal of causal modeling is to unravel enough of the data generating process to be able to make predictions of the consequences of actions (also called interventions, experiments or manipulations) performed by an external agent.

Author Information

Isabelle Guyon (Google and ChaLearn)

Isabelle Guyon recently joined Google Brain as a research scientist. She is also professor of artificial intelligence at Université Paris-Saclay (Orsay). Her areas of expertise include computer vision, bioinformatics, and power systems. She is best known for being a co-inventor of Support Vector Machines. Her recent interests are in automated machine learning, meta-learning, and data-centric AI. She has been a strong promoter of challenges and benchmarks, and is president of ChaLearn, a non-profit dedicated to organizing machine learning challenges. She is community lead of Codalab competitions, a challenge platform used both in academia and industry. She co-organized the “Challenges in Machine Learning Workshop” @ NeurIPS between 2014 and 2019, launched the "NeurIPS challenge track" in 2017 while she was general chair, and pushed the creation of the "NeurIPS datasets and benchmark track" in 2021, as a NeurIPS board member.

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