Lagrangian theory of gravitational instability of Friedman-Lematre cosmologies - a generic third-order model for non-linear clustering
|
journal
|
April 1994 |
Physics 101: Learning Physical Object Properties from Unlabeled Videos
|
conference
|
January 2016 |
Densely Connected Convolutional Networks
|
preprint
|
January 2016 |
Photometric Supernova Classification With Machine Learning
|
text
|
January 2016 |
The Sdss-Iv Extended Baryon Oscillation Spectroscopic Survey: Overview and Early data
|
journal
|
February 2016 |
Cosmology and Fundamental Physics with the Euclid Satellite
|
journal
|
September 2013 |
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|
journal
|
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|
journal
|
July 2018 |
Mastering the game of Go with deep neural networks and tree search
|
journal
|
January 2016 |
A New Parallel P3M Code for Very Large-Scale Cosmological Simulations
|
text
|
January 1998 |
TreePM: A code for cosmological N-body simulations
|
journal
|
December 2002 |
The Zel'dovich approximation
|
journal
|
February 2014 |
U-Net: Convolutional Networks for Biomedical Image Segmentation
- Ronneberger, Olaf; Fischer, Philipp; Brox, Thomas
-
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III
https://doi.org/10.1007/978-3-319-24574-4_28
|
book
|
November 2015 |
The Zeldovich approximation
|
text
|
January 2014 |
Learning Physical Intuition of Block Towers by Example
|
preprint
|
January 2016 |
Deep learning for regulatory genomics
|
journal
|
August 2015 |
Lagrangian theory of gravitational instability of Friedman-Lemaitre cosmologies - generic third-order model for non-linear clustering
|
text
|
January 1993 |
Ready or Not, Here We Go
|
journal
|
June 2016 |
Long-term Recurrent Convolutional Networks for Visual Recognition and Description
|
preprint
|
January 2014 |
Human-level control through deep reinforcement learning
|
journal
|
February 2015 |
Cosmology and fundamental physics with the Euclid satellite
|
text
|
January 2012 |
Cosmology and Fundamental Physics with the Euclid Satellite
|
journal
|
September 2013 |
Simulation as an engine of physical scene understanding
|
journal
|
October 2013 |
Cosmology and fundamental physics with the Euclid satellite
|
text
|
January 2018 |
Planck 2015 results : XXIII. The thermal Sunyaev-Zeldovich effect-cosmic infrared background correlation
|
journal
|
September 2016 |
Planck 2015 results. XIII. Cosmological parameters
|
text
|
January 2015 |
FastPM: a new scheme for fast simulations of dark matter and haloes
|
journal
|
August 2016 |
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning
|
journal
|
July 2015 |
Planck 2015 results : XIII. Cosmological parameters
|
journal
|
September 2016 |
Planning chemical syntheses with deep neural networks and symbolic AI
|
journal
|
March 2018 |
Planning chemical syntheses with deep neural networks and symbolic AI
|
journal
|
March 2018 |
Long-term recurrent convolutional networks for visual recognition and description
|
conference
|
June 2015 |
AI designs organic syntheses
|
journal
|
March 2018 |
Simulation as an engine of physical scene understanding
|
journal
|
October 2013 |
Exploring the posterior surface of the large scale structure reconstruction
|
journal
|
July 2018 |
Learning Visual Predictive Models of Physics for Playing Billiards
|
preprint
|
January 2015 |
Bayesian physical reconstruction of initial conditions from large-scale structure surveys
|
journal
|
April 2013 |
The Baryon Oscillation Spectroscopic Survey of Sdss-Iii
|
journal
|
December 2012 |
Planck 2015 results : XXVI. The Second
|
journal
|
September 2016 |
Galaxy And Mass Assembly (GAMA): end of survey report and data release 2
|
journal
|
July 2015 |
A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues
|
journal
|
November 2018 |
DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications
|
journal
|
April 2019 |
Long-Term Recurrent Convolutional Networks for Visual Recognition and Description
|
journal
|
April 2017 |
Accelerating Eulerian Fluid Simulation With Convolutional Networks
|
preprint
|
January 2016 |
The Baryon Oscillation Spectroscopic Survey of SDSS-III
|
text
|
January 2012 |
Deep learning
|
journal
|
May 2015 |
A new parallel code for very large-scale cosmological simulations
|
journal
|
December 1998 |
CMU DeepLens: deep learning for automatic image-based galaxy–galaxy strong lens finding
|
journal
|
July 2017 |
CosmoFlow: Using Deep Learning to Learn the Universe at Scale
|
conference
|
November 2018 |
The 2dF Galaxy Redshift Survey: spectra and redshifts
|
journal
|
December 2001 |
Sdss-Iii: Massive Spectroscopic Surveys of the Distant Universe, the Milky way, and Extra-Solar Planetary Systems
|
journal
|
August 2011 |
Planck 2015 results : XVI. Isotropy and statistics of the CMB
|
journal
|
September 2016 |
Bayesian physical reconstruction of initial conditions from large-scale structure surveys
|
journal
|
April 2013 |
Cosmology and fundamental physics with the Euclid satellite
|
journal
|
April 2018 |
GADGET: a code for collisionless and gasdynamical cosmological simulations
|
journal
|
April 2001 |
Fast automated analysis of strong gravitational lenses with convolutional neural networks
|
journal
|
August 2017 |
Planck 2015 results : X. Diffuse component separation: Foreground maps
|
journal
|
September 2016 |
How filaments of galaxies are woven into the cosmic web
|
journal
|
April 1996 |
The 6dF Galaxy Survey: final redshift release (DR3) and southern large-scale structures
|
journal
|
October 2009 |
The initial conditions of the Universe from constrained simulations
|
journal
|
November 2012 |
Exploring the posterior surface of the large scale structure reconstruction
|
text
|
January 2018 |
Opportunities and obstacles for deep learning in biology and medicine
|
journal
|
April 2018 |
A volumetric deep Convolutional Neural Network for simulation of mock dark matter halo catalogues
|
text
|
January 2018 |
Machine learning for quantum physics
|
journal
|
February 2017 |
Opportunities and obstacles for deep learning in biology and medicine
|
posted_content
|
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The SDSS-IV extended Baryon Oscillation Spectroscopic Survey: Overview and Early Data
|
text
|
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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
|
preprint
|
January 2016 |
Fast automated analysis of strong gravitational lenses with convolutional neural networks
|
journal
|
August 2017 |
Deep learning
|
journal
|
May 2015 |
Deep Learning
|
text
|
January 2018 |
Helmholtz decomposition of the Lagrangian displacement
|
journal
|
April 2014 |
Photometric Supernova Classification with Machine Learning
|
journal
|
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nbodykit: An Open-source, Massively Parallel Toolkit for Large-scale Structure
|
journal
|
September 2018 |
Solving the quantum many-body problem with artificial neural networks
|
journal
|
February 2017 |
Computing the three-point correlation function of galaxies in $\mathcal {O}(N^2)$ time
|
journal
|
October 2015 |
Star–galaxy classification using deep convolutional neural networks
|
journal
|
October 2016 |
Galaxy And Mass Assembly (GAMA): end of survey report and data release 2
|
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|
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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
|
conference
|
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The evolution of large-scale structure in a universe dominated by cold dark matter
|
journal
|
May 1985 |
Densely Connected Convolutional Networks
|
conference
|
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Computing the Three-Point Correlation Function of Galaxies in $\mathcal{O}(N^2)$ Time
|
text
|
January 2015 |
DeepSphere: Efficient spherical convolutional neural network with HEALPix sampling for cosmological applications
|
journal
|
April 2019 |
DeepCMB: Lensing reconstruction of the cosmic microwave background with deep neural networks
|
journal
|
July 2019 |
Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images
|
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|
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TreePM: A code for cosmological N-body simulations
|
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|
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