Universal Marginalizer for Amortised Inference and Embedding of Generative Models

Autor: Walecki, Robert, Buchard, Albert, Gourgoulias, Kostis, Hart, Chris, Lomeli, Maria, Navarro, A. K. W., Zwiessele, Max, Perov, Yura, Johri, Saurabh

Probabilistic graphical models are powerful tools which allow us to formalise our knowledge about the world and reason about its inherent uncertainty. There exist a considerable number of methods for performing inference in probabilistic graphical mo

Externí odkaz: http://arxiv.org/abs/1811.04727

The Multivariate Generalised von Mises Distribution: Inference and Applications

Autor: Navarro, Alexandre K. W., Frellsen, Jes, Turner, Richard E.

Publikováno v: Navarro, A K W, Frellsen, J & Turner, R 2017, The Multivariate Generalised von Mises Distribution: Inference and Applications . in Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17) . AAAI Press, pp. 2394-2400 . < https://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/15020/14421 >

Circular variables arise in a multitude of data-modelling contexts ranging from robotics to the social sciences, but they have been largely overlooked by the machine learning community. This paper partially redresses this imbalance by extending some

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::68e439bff11fea76d87248d32ba1f710
https://pure.itu.dk/ws/files/82476959/main_frellsen.pdf

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