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  • title: From Predictive to Caussal Modeling: Bridging the Gap
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            From Predictive to Caussal Modeling: Bridging the Gap
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            From Predictive to Caussal Modeling: Bridging the Gap

            Jun 15, 2019

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            Caroline Uhler

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            About

            Graph-structured representations are widely used as a natural and powerful way to encode information such as relations between objects or entities, interactions between online users (e.g., in social networks), 3D meshes in computer graphics, multi-agent environments, as well as molecular structures, to name a few. Learning and reasoning with graph-structured representations is gaining increasing interest in both academia and industry, due to its fundamental advantages over more traditional unstr…

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            ICML 2019

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            About ICML 2019

            The International Conference on Machine Learning (ICML) is the premier gathering of professionals dedicated to the advancement of the branch of artificial intelligence known as machine learning. ICML is globally renowned for presenting and publishing cutting-edge research on all aspects of machine learning used in closely related areas like artificial intelligence, statistics and data science, as well as important application areas such as machine vision, computational biology, speech recognition, and robotics. ICML is one of the fastest growing artificial intelligence conferences in the world. Participants at ICML span a wide range of backgrounds, from academic and industrial researchers, to entrepreneurs and engineers, to graduate students and postdocs.

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