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1
Practical galaxy morphology tools from deep supervised representation learning
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Artigo
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Practical galaxy morphology tools from deep supervised representation learning

Walmsley, Mike ; Scaife, Anna M M ; Lintott, Chris ; Lochner, Michelle ; Etsebeth, Verlon ; Géron, Tobias ; Dickinson, Hugh ; Fortson, Lucy ; Kruk, Sandor ; Masters, Karen L ; Mantha, Kameswara Bharadwaj ; Simmons, Brooke D

Monthly notices of the Royal Astronomical Society, 2022-05, Vol.513 (2), p.1581-1599 [Periódico revisado por pares]

United States: Oxford University Press

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2
sofia 2 – an automated, parallel H i source finding pipeline for the WALLABY survey
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sofia 2 – an automated, parallel H i source finding pipeline for the WALLABY survey

Westmeier, T ; Kitaeff, S ; Pallot, D ; Serra, P ; van der Hulst, J M ; Jurek, R J ; Elagali, A ; For, B-Q ; Kleiner, D ; Koribalski, B S ; Lee-Waddell, K ; Mould, J R ; Reynolds, T N ; Rhee, J ; Staveley-Smith, L

Monthly notices of the Royal Astronomical Society, 2021-09, Vol.506 (3), p.3962-3976 [Periódico revisado por pares]

Oxford University Press

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3
A review of statistical methods for dietary pattern analysis
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Artigo
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A review of statistical methods for dietary pattern analysis

Zhao, Junkang ; Li, Zhiyao ; Gao, Qian ; Zhao, Haifeng ; Chen, Shuting ; Huang, Lun ; Wang, Wenjie ; Wang, Tong

Nutrition journal, 2021-04, Vol.20 (1), p.37-37, Article 37 [Periódico revisado por pares]

England: BioMed Central Ltd

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4
Analysis of Early Science observations with the CHaracterising ExOPlanets Satellite (CHEOPS) using pycheops
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Artigo
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Analysis of Early Science observations with the CHaracterising ExOPlanets Satellite (CHEOPS) using pycheops

Maxted, P F L ; Ehrenreich, D ; Wilson, T G ; Alibert, Y ; Cameron, A Collier ; Hoyer, S ; Sousa, S G ; Olofsson, G ; Bekkelien, A ; Deline, A ; Delrez, L ; Bonfanti, A ; Borsato, L ; Alonso, R ; Anglada Escudé, G ; Barrado, D ; Barros, S C C ; Baumjohann, W ; Beck, M ; Beck, T ; Benz, W ; Billot, N ; Biondi, F ; Bonfils, X ; Brandeker, A ; Broeg, C ; Bárczy, T ; Cabrera, J ; Charnoz, S ; Corral Van Damme, C ; Csizmadia, Sz ; Davies, M B ; Deleuil, M ; Demangeon, O D S ; Demory, B-O ; Erikson, A ; Florén, H G ; Fortier, A ; Fossati, L ; Fridlund, M ; Futyan, D ; Gandolfi, D ; Gillon, M ; Guedel, M ; Guterman, P ; Heng, K ; Isaak, K G ; Kiss, L ; Laskar, J ; Lecavelier des Etangs, A ; Lendl, M ; Lovis, C ; Magrin, D ; Nascimbeni, V ; Ottensamer, R ; Pagano, I ; Pallé, E ; Peter, G ; Piotto, G ; Pollacco, D ; Pozuelos, F J ; Queloz, D ; Ragazzoni, R ; Rando, N ; Rauer, H ; Reimers, C ; Ribas, I ; Salmon, S ; Santos, N C ; Scandariato, G ; Simon, A E ; Smith, A M S ; Steller, M ; Swayne, M I ; Szabó, Gy M ; Ségransan, D ; Thomas, N ; Udry, S ; Van Grootel, V ; Walton, N A

Monthly notices of the Royal Astronomical Society, 2022, Vol.514 (1), p.77-104 [Periódico revisado por pares]

United Kingdom: Oxford University Press

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5
Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies
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Artigo
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Galaxy Zoo DECaLS: Detailed visual morphology measurements from volunteers and deep learning for 314 000 galaxies

Walmsley, Mike ; Lintott, Chris ; Géron, Tobias ; Kruk, Sandor ; Krawczyk, Coleman ; Willett, Kyle W ; Bamford, Steven ; Kelvin, Lee S ; Fortson, Lucy ; Gal, Yarin ; Keel, William ; Masters, Karen L ; Mehta, Vihang ; Simmons, Brooke D ; Smethurst, Rebecca ; Smith, Lewis ; Baeten, Elisabeth M ; Macmillan, Christine

Monthly notices of the Royal Astronomical Society, 2022-01, Vol.509 (3), p.3966-3988 [Periódico revisado por pares]

United States: Oxford University Press

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6
A machine learning approach to galaxy properties: joint redshift–stellar mass probability distributions with Random Forest
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Artigo
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A machine learning approach to galaxy properties: joint redshift–stellar mass probability distributions with Random Forest

Mucesh, S ; Hartley, W G ; Palmese, A ; Lahav, O ; Whiteway, L ; Bluck, A F L ; Alarcon, A ; Amon, A ; Bechtol, K ; Bernstein, G M ; Carnero Rosell, A ; Carrasco Kind, M ; Choi, A ; Eckert, K ; Everett, S ; Gruen, D ; Gruendl, R A ; Harrison, I ; Huff, E M ; Kuropatkin, N ; Sevilla-Noarbe, I ; Sheldon, E ; Yanny, B ; Aguena, M ; Allam, S ; Bacon, D ; Bertin, E ; Bhargava, S ; Brooks, D ; Carretero, J ; Castander, F J ; Conselice, C ; Costanzi, M ; Crocce, M ; da Costa, L N ; Pereira, M E S ; De Vicente, J ; Desai, S ; Diehl, H T ; Drlica-Wagner, A ; Evrard, A E ; Ferrero, I ; Flaugher, B ; Fosalba, P ; Frieman, J ; García-Bellido, J ; Gaztanaga, E ; Gerdes, D W ; Gschwend, J ; Gutierrez, G ; Hinton, S R ; Hollowood, D L ; Honscheid, K ; James, D J ; Kuehn, K ; Lima, M ; Lin, H ; Maia, M A G ; Melchior, P ; Menanteau, F ; Miquel, R ; Morgan, R ; Paz-Chinchón, F ; Plazas, A A ; Sanchez, E ; Scarpine, V ; Schubnell, M ; Serrano, S ; Smith, M ; Suchyta, E ; Tarle, G ; Thomas, D ; To, C ; Varga, T N ; Wilkinson, R D

Monthly notices of the Royal Astronomical Society, 2021-04, Vol.502 (2), p.2770-2786 [Periódico revisado por pares]

United States: Oxford University Press

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7
The International Pulsar Timing Array: First data release
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Artigo
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The International Pulsar Timing Array: First data release

Verbiest, J. P. W ; Lentati, L ; Hobbs, G ; van Haasteren, R ; Demorest, P. B ; Janssen, G. H ; Wang, J.-B ; Desvignes, G ; Caballero, R. N ; Keith, M. J ; Champion, D. J ; Arzoumanian, Z ; Babak, S ; Bassa, C. G ; Bhat, N. D. R ; Brazier, A ; Brem, P ; Burgay, M ; Burke-Spolaor, S ; Chamberlin, S. J ; Chatterjee, S ; Christy, B ; Cognard, I ; Cordes, J. M ; Dai, S ; Dolch, T ; Ellis, J. A ; Ferdman, R. D ; Fonseca, E ; Gair, J. R ; Garver-Daniels, N. E ; Gentile, P ; Gonzalez, M. E ; Graikou, E ; Guillemot, L ; Hessels, J. W. T ; Jones, G ; Karuppusamy, R ; Kerr, M ; Kramer, M ; Lam, M. T ; Lasky, P. D ; Lassus, A ; Lazarus, P ; Lazio, T. J. W ; Lee, K. J ; Levin, L ; Liu, K ; Lynch, R. S ; Lyne, A. G ; Mckee, J ; McLaughlin, M. A ; McWilliams, S. T ; Madison, D. R ; Manchester, R. N ; Mingarelli, C. M. F ; Nice, D. J ; Osłowski, S ; Palliyaguru, N. T ; Pennucci, T. T ; Perera, B. B. P ; Perrodin, D ; Possenti, A ; Petiteau, A ; Ransom, S. M ; Reardon, D ; Rosado, P. A ; Sanidas, S. A ; Sesana, A ; Shaifullah, G ; Shannon, R. M ; Siemens, X ; Simon, J ; Smits, R ; Spiewak, R ; Stairs, I. H ; Stappers, B. W ; Stinebring, D. R ; Stovall, K ; Swiggum, J. K ; Taylor, S. R ; Theureau, G ; Tiburzi, C ; Toomey, L ; Vallisneri, M ; van Straten, W ; Vecchio, A ; Wang, Y ; Wen, L ; You, X. P ; Zhu, W. W ; Zhu, X.-J

Monthly notices of the Royal Astronomical Society, 2016-05, Vol.458 (2), p.1267-1288 [Periódico revisado por pares]

London: Oxford University Press

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8
Ensemble feature selection for high-dimensional data: a stability analysis across multiple domains
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Ensemble feature selection for high-dimensional data: a stability analysis across multiple domains

Pes, Barbara

Neural computing & applications, 2020-05, Vol.32 (10), p.5951-5973 [Periódico revisado por pares]

London: Springer London

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9
Compositional data analysis for physical activity, sedentary time and sleep research
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Artigo
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Compositional data analysis for physical activity, sedentary time and sleep research

Dumuid, Dorothea ; Stanford, Tyman E ; Martin-Fernández, Josep-Antoni ; Pedišić, Željko ; Maher, Carol A ; Lewis, Lucy K ; Hron, Karel ; Katzmarzyk, Peter T ; Chaput, Jean-Philippe ; Fogelholm, Mikael ; Hu, Gang ; Lambert, Estelle V ; Maia, José ; Sarmiento, Olga L ; Standage, Martyn ; Barreira, Tiago V ; Broyles, Stephanie T ; Tudor-Locke, Catrine ; Tremblay, Mark S ; Olds, Timothy

Statistical methods in medical research, 2018-12, Vol.27 (12), p.3726-3738 [Periódico revisado por pares]

London, England: SAGE Publications

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10
Deep learning improves identification of Radio Frequency Interference
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Deep learning improves identification of Radio Frequency Interference

Vafaei Sadr, Alireza ; Bassett, Bruce A ; Oozeer, Nadeem ; Fantaye, Yabebal ; Finlay, Chris

Monthly notices of the Royal Astronomical Society, 2020-11, Vol.499 (1), p.379-390 [Periódico revisado por pares]

Oxford University Press

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