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Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
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Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning

Cote-Allard, Ulysse ; Fall, Cheikh Latyr ; Drouin, Alexandre ; Campeau-Lecours, Alexandre ; Gosselin, Clement ; Glette, Kyrre ; Laviolette, Francois ; Gosselin, Benoit

IEEE transactions on neural systems and rehabilitation engineering, 2019-04, Vol.27 (4), p.760-771 [Periódico revisado por pares]

United States: IEEE

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2
Colloquium : Machine learning in nuclear physics
Colloquium : Machine learning in nuclear physics
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Colloquium : Machine learning in nuclear physics

Boehnlein, Amber ; Diefenthaler, Markus ; Sato, Nobuo ; Schram, Malachi ; Ziegler, Veronique ; Fanelli, Cristiano ; Hjorth-Jensen, Morten ; Horn, Tanja ; Kuchera, Michelle P. ; Lee, Dean ; Nazarewicz, Witold ; Ostroumov, Peter ; Orginos, Kostas ; Poon, Alan ; Wang, Xin-Nian ; Scheinker, Alexander ; Smith, Michael S. ; Pang, Long-Gang

Reviews of modern physics, 2022-09, Vol.94 (3), p.1, Article 031003 [Periódico revisado por pares]

College Park: American Institute of Physics

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3
Designing deep learning studies in cancer diagnostics
Designing deep learning studies in cancer diagnostics
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Designing deep learning studies in cancer diagnostics

Kleppe, Andreas ; Skrede, Ole-Johan ; De Raedt, Sepp ; Liestøl, Knut ; Kerr, David J ; Danielsen, Håvard E

Nature reviews. Cancer, 2021-03, Vol.21 (3), p.199-211 [Periódico revisado por pares]

England: Nature Publishing Group

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4
Direct shape optimization through deep reinforcement learning
Direct shape optimization through deep reinforcement learning
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Direct shape optimization through deep reinforcement learning

Viquerat, Jonathan ; Rabault, Jean ; Kuhnle, Alexander ; Ghraieb, Hassan ; Larcher, Aurélien ; Hachem, Elie

Journal of computational physics, 2021-03, Vol.428, p.110080, Article 110080 [Periódico revisado por pares]

Cambridge: Elsevier Inc

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5
Learning Poker in Different Communities of Practice: A Qualitative Analysis of Poker Players’ Learning Processes and the Norms in Different Learning Communities
Learning Poker in Different Communities of Practice: A Qualitative Analysis of Poker Players’ Learning Processes and the Norms in Different Learning Communities
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Learning Poker in Different Communities of Practice: A Qualitative Analysis of Poker Players’ Learning Processes and the Norms in Different Learning Communities

Talberg, Niri

Journal of gambling issues, 2019, Vol.42 [Periódico revisado por pares]

Centre for Addiction and Mental Health

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6
Finding quadruply imaged quasars with machine learning – I. Methods
Finding quadruply imaged quasars with machine learning – I. Methods
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Finding quadruply imaged quasars with machine learning – I. Methods

Akhazhanov, A ; More, A ; Amini, A ; Hazlett, C ; Treu, T ; Birrer, S ; Shajib, A ; Liao, K ; Lemon, C ; Agnello, A ; Nord, B ; Aguena, M ; Allam, S ; Andrade-Oliveira, F ; Annis, J ; Brooks, D ; Buckley-Geer, E ; Burke, D L ; Carnero Rosell, A ; Carrasco Kind, M ; Carretero, J ; Choi, A ; Conselice, C ; Costanzi, M ; da Costa, L N ; Pereira, M E S ; De Vicente, J ; Desai, S ; Dietrich, J P ; Doel, P ; Everett, S ; Ferrero, I ; Finley, D A ; Flaugher, B ; Frieman, J ; García-Bellido, J ; Gerdes, D W ; Gruen, D ; Gruendl, R A ; Gschwend, J ; Gutierrez, G ; Hinton, S R ; Hollowood, D L ; Honscheid, K ; James, D J ; Kim, A G ; Kuehn, K ; Kuropatkin, N ; Lahav, O ; Lima, M ; Lin, H ; Maia, M A G ; March, M ; Menanteau, F ; Miquel, R ; Morgan, R ; Palmese, A ; Paz-Chinchón, F ; Pieres, A ; Plazas Malagón, A A ; Sanchez, E ; Scarpine, V ; Serrano, S ; Sevilla-Noarbe, I ; Smith, M ; Soares-Santos, M ; Suchyta, E ; Swanson, M E C ; Tarle, G ; To, C ; Varga, T N ; Weller, J

Monthly notices of the Royal Astronomical Society, 2022-05, Vol.513 (2), p.2407-2421 [Periódico revisado por pares]

United Kingdom: Oxford University Press

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7
Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
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Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Nunes, Abraham ; Schnack, Hugo G ; Ching, Christopher R K ; Agartz, Ingrid ; Akudjedu, Theophilus N ; Alda, Martin ; Alnæs, Dag ; Alonso-Lana, Silvia ; Bauer, Jochen ; Baune, Bernhard T ; Bøen, Erlend ; Bonnin, Caterina Del Mar ; Busatto, Geraldo F ; Canales-Rodríguez, Erick J ; Cannon, Dara M ; Caseras, Xavier ; Chaim-Avancini, Tiffany M ; Dannlowski, Udo ; Díaz-Zuluaga, Ana M ; Dietsche, Bruno ; Doan, Nhat Trung ; Duchesnay, Edouard ; Elvsåshagen, Torbjørn ; Emden, Daniel ; Eyler, Lisa T ; Fatjó-Vilas, Mar ; Favre, Pauline ; Foley, Sonya F ; Fullerton, Janice M ; Glahn, David C ; Goikolea, Jose M ; Grotegerd, Dominik ; Hahn, Tim ; Henry, Chantal ; Hibar, Derrek P ; Houenou, Josselin ; Howells, Fleur M ; Jahanshad, Neda ; Kaufmann, Tobias ; Kenney, Joanne ; Kircher, Tilo T J ; Krug, Axel ; Lagerberg, Trine V ; Lenroot, Rhoshel K ; López-Jaramillo, Carlos ; Machado-Vieira, Rodrigo ; Malt, Ulrik F ; McDonald, Colm ; Mitchell, Philip B ; Mwangi, Benson ; Nabulsi, Leila ; Opel, Nils ; Overs, Bronwyn J ; Pineda-Zapata, Julian A ; Pomarol-Clotet, Edith ; Redlich, Ronny ; Roberts, Gloria ; Rosa, Pedro G ; Salvador, Raymond ; Satterthwaite, Theodore D ; Soares, Jair C ; Stein, Dan J ; Temmingh, Henk S ; Trappenberg, Thomas ; Uhlmann, Anne ; van Haren, Neeltje E M ; Vieta, Eduard ; Westlye, Lars T ; Wolf, Daniel H ; Yüksel, Dilara ; Zanetti, Marcus V ; Andreassen, Ole A ; Thompson, Paul M ; Hajek, Tomas

Molecular psychiatry, 2020-09, Vol.25 (9), p.2130-2143 [Periódico revisado por pares]

England: Nature Publishing Group

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8
Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images
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Euclid preparation – XXIII. Derivation of galaxy physical properties with deep machine learning using mock fluxes and H-band images

Cavuoti, S ; Humphrey, A ; Hunt, L K ; Tortora, C ; Auricchio, N ; Bender, R ; Branchini, E ; Brinchmann, J ; Camera, S ; Capobianco, V ; Castellano, M ; Conversi, L ; Corcione, L ; Degaudenzi, H ; Douspis, M ; Dubath, F ; Duncan, C A J ; Dupac, X ; Dusini, S ; Farrens, S ; Frailis, M ; Fumana, M ; Garilli, B ; Gillard, W ; Gillis, B ; Grupp, F ; Hornstrup, A ; Jahnke, K ; Kümmel, M ; Kohley, R ; Kunz, M ; Kurki-Suonio, H ; Ligori, S ; Maiorano, E ; Mansutti, O ; Marggraf, O ; Markovic, K ; Marulli, F ; Maurogordato, S ; Medinaceli, E ; Meneghetti, M ; Merlin, E ; Meylan, G ; Moscardini, L ; Munari, E ; Niemi, S M ; Padilla, C ; Paltani, S ; Pasian, F ; Polenta, G ; Poncet, M ; Renzi, A ; Rhodes, J ; Riccio, G ; Sartoris, B ; Schneider, P ; Scodeggio, M ; Secroun, A ; Seidel, G ; Sirignano, C ; Stanco, L ; Tavagnacco, D ; Taylor, A N ; Tereno, I ; Toledo-Moreo, R ; Tutusaus, I ; Valentijn, E A ; Valenziano, L ; Zacchei, A ; Zamorani, G ; Andreon, S ; Boucaud, A ; Graciá-Carpio, J ; Maino, D ; Mei, S ; Scottez, V ; Tenti, M ; Ballardini, M ; Biviano, A ; Cappi, A ; Casas, S ; Cuby, J ; Escoffier, S ; Ganga, K ; Gozaliasl, G ; Hildebrandt, H ; Kansal, V ; Loureiro, A ; Macías-Pérez, J F ; Mainetti, G ; Marcin, S ; Martinelli, M ; Metcalf, R B ; Patrizii, L ; Peel, A ; Potter, D ; Sakr, Z ; Schirmer, M ; Sereno, M ; Valiviita, J

Monthly notices of the Royal Astronomical Society, 2023-02, Vol.520 (3), p.3529-3548 [Periódico revisado por pares]

Oxford University Press

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9
On instabilities of deep learning in image reconstruction and the potential costs of AI
On instabilities of deep learning in image reconstruction and the potential costs of AI
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On instabilities of deep learning in image reconstruction and the potential costs of AI

Antun, Vegard ; Renna, Francesco ; Poon, Clarice ; Adcock, Ben ; Hansen, Anders C.

Proceedings of the National Academy of Sciences - PNAS, 2020-12, Vol.117 (48), p.30088-30095 [Periódico revisado por pares]

United States: National Academy of Sciences

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Opening up the black box: Teacher competence, instructional quality, and students’ learning progress
Opening up the black box: Teacher competence, instructional quality, and students’ learning progress
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Opening up the black box: Teacher competence, instructional quality, and students’ learning progress

Blömeke, Sigrid ; Jentsch, Armin ; Ross, Natalie ; Kaiser, Gabriele ; König, Johannes

Learning and instruction, 2022-06, Vol.79, p.101600, Article 101600 [Periódico revisado por pares]

Elsevier Ltd

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