Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Kalaitzis, Alfredo"'
Autor:
Deudon, Michel, Kalaitzis, Alfredo, Goytom, Israel, Arefin, Md Rifat, Lin, Zhichao, Sankaran, Kris, Michalski, Vincent, Kahou, Samira E., Cornebise, Julien, Bengio, Yoshua
Generative deep learning has sparked a new wave of Super-Resolution (SR) algorithms that enhance single images with impressive aesthetic results, albeit with imaginary details. Multi-frame Super-Resolution (MFSR) offers a more grounded approach to th
Externí odkaz:
http://arxiv.org/abs/2002.06460
Autor:
Jungbluth, Anna, Gitiaux, Xavier, Maloney, Shane A., Shneider, Carl, Wright, Paul J., Kalaitzis, Alfredo, Deudon, Michel, Baydin, Atılım Güneş, Gal, Yarin, Muñoz-Jaramillo, Andrés
Breakthroughs in our understanding of physical phenomena have traditionally followed improvements in instrumentation. Studies of the magnetic field of the Sun, and its influence on the solar dynamo and space weather events, have benefited from improv
Externí odkaz:
http://arxiv.org/abs/1911.01490
Autor:
Gitiaux, Xavier, Maloney, Shane A., Jungbluth, Anna, Shneider, Carl, Wright, Paul J., Baydin, Atılım Güneş, Deudon, Michel, Gal, Yarin, Kalaitzis, Alfredo, Muñoz-Jaramillo, Andrés
Machine learning techniques have been successfully applied to super-resolution tasks on natural images where visually pleasing results are sufficient. However in many scientific domains this is not adequate and estimations of errors and uncertainties
Externí odkaz:
http://arxiv.org/abs/1911.01486
Autor:
Lamb, Kara, Malhotra, Garima, Vlontzos, Athanasios, Wagstaff, Edward, Baydin, Atılım Günes, Bhiwandiwalla, Anahita, Gal, Yarin, Kalaitzis, Alfredo, Reina, Anthony, Bhatt, Asti
High energy particles originating from solar activity travel along the the Earth's magnetic field and interact with the atmosphere around the higher latitudes. These interactions often manifest as aurora in the form of visible light in the Earth's io
Externí odkaz:
http://arxiv.org/abs/1910.03085
Autor:
Lamb, Kara, Malhotra, Garima, Vlontzos, Athanasios, Wagstaff, Edward, Baydin, Atılım Günes, Bhiwandiwalla, Anahita, Gal, Yarin, Kalaitzis, Alfredo, Reina, Anthony, Bhatt, Asti
A Global Navigation Satellite System (GNSS) uses a constellation of satellites around the earth for accurate navigation, timing, and positioning. Natural phenomena like space weather introduce irregularities in the Earth's ionosphere, disrupting the
Externí odkaz:
http://arxiv.org/abs/1910.01570
Autor:
Delisle, Laure, Kalaitzis, Alfredo, Majewski, Krzysztof, de Berker, Archy, Marin, Milena, Cornebise, Julien
We report the first, to the best of our knowledge, hand-in-hand collaboration between human rights activists and machine learners, leveraging crowd-sourcing to study online abuse against women on Twitter. On a technical front, we carefully curate an
Externí odkaz:
http://arxiv.org/abs/1902.03093
Autor:
Kalaitzis, Alfredo
We study structured covariance matrices in a Gaussian setting for a variety of data analysis scenarios. Despite its simplistic nature, we argue for the broad applicability of the Gaussian family through its second order statistics. We focus on three
Externí odkaz:
http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.574078
Autor:
Kalaitzis, Alfredo, Silva, Ricardo
Learning the joint dependence of discrete variables is a fundamental problem in machine learning, with many applications including prediction, clustering and dimensionality reduction. More recently, the framework of copula modeling has gained popular
Externí odkaz:
http://arxiv.org/abs/1306.2685
Autor:
Kalaitzis, Alfredo, Lawrence, Neil
Probabilistic principal component analysis (PPCA) seeks a low dimensional representation of a data set in the presence of independent spherical Gaussian noise. The maximum likelihood solution for the model is an eigenvalue problem on the sample covar
Externí odkaz:
http://arxiv.org/abs/1206.4560
Probabilistic principal component analysis (PPCA) seeks a low dimensional representation of a data set in the presence of independent spherical Gaussian noise, Sigma = (sigma^2)*I. The maximum likelihood solution for the model is an eigenvalue proble
Externí odkaz:
http://arxiv.org/abs/1106.4333