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A grand challenge of the 21st century cosmology is to accurately estimate the cosmological parameters of our Universe.
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Efficient computation of CMB anisotropies in closed FRW models
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The cosmological simulation code GADGET-2
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Introduction to nonparametric estimation
Tsybakov, Alexandre B · 2008
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Learning deep architectures for ai
Bengio, Yoshua · 2009
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Erhan, Dumitru, Bengio, Yoshua, Courville, Aaron, and Vincent, Pascal · 2009
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Estimation and detection of functions from anisotropic sobolev classes
Ingster, Y. and Stepanova, N · 2011
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Hinton, Geoffrey E, Srivastava, Nitish, Krizhevsky, Alex, Sutskever, Ilya, and Salakhutdinov, Ruslan R · 2012
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Imagenet classification with deep convolutional neural networks
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Gens, Robert and Domingos, Pedro M · 2014
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Adam: A method for stochastic optimization
Kingma, Diederik and Ba, Jimmy · 2014
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Fast distribution to real regression
Oliva, Junier B, Neiswanger, Willie, Poczos, Barnabas, Schneider, Jeff, and Xing, Eric · 2014
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The Eleventh and Twelfth Data Releases of the Sloan Digital Sky Survey: Final Data from SDSS-III
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Rotation-invariant convolutional neural networks for galaxy morphology prediction
Dieleman, Sander, Willett, Kyle W, and Dambre, Joni · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
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Rectifier nonlinearities improve neural network acoustic models
Maas, Andrew L, Hannun, Awni Y, and Ng, Andrew Y · 2013
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Multi-scale 3d convolutional neural networks for lesion segmentation in brain mri
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Planck 2015 results. XIII. Cosmological parameters
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