Zobrazeno 1 - 10
of 15 881
pro vyhledávání: '"Jarvis, —d"'
Autor:
Killestein, T. L., Kelsey, L., Wickens, E., Nuttall, L., Lyman, J., Krawczyk, C., Ackley, K., Dyer, M. J., Jiménez-Ibarra, F., Ulaczyk, K., O'Neill, D., Kumar, A., Steeghs, D., Galloway, D. K., Dhillon, V. S., O'Brien, P., Ramsay, G., Noysena, K., Kotak, R., Breton, R. P., Pallé, E., Pollacco, D., Awiphan, S., Belkin, S., Chote, P., Clark, P., Coppejans, D., Duffy, C., Eyles-Ferris, R., Godson, B., Gompertz, B., Graur, O., Irawati, P., Jarvis, D., Julakanti, Y., Kennedy, M. R., Kuncarayakti, H., Levan, A., Littlefair, S., Magee, M., Mandhai, S., Sánchez, D. Mata, Mattila, S., McCormac, J., Mullaney, J., Munday, J., Patel, M., Pursiainen, M., Rana, J., Sawangwit, U., Stanway, E., Starling, R., Warwick, B., Wiersema, K.
Time-domain astrophysics continues to grow rapidly, with the inception of new surveys drastically increasing data volumes. Democratised, distributed approaches to training sets for machine learning classifiers are crucial to make the most of this tor
Externí odkaz:
http://arxiv.org/abs/2406.02334
Akademický článek
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Autor:
Badorrek, P., Broeders, M., Boersma, W.G., Chetta, A., Cukier, A., D'Amato, M., Djukanovic, R., Foschino, M.P., Gessner, C., Hanania, N., Martin, R., Milleri, S., Olivenstein, R., Paggiaro, P., Pizzichini, E., Plaza Moral, V., Postma, D.S., Scichilone, N., Schilz, R., Spanevello, A., Stelmach, R., Vroegop, J.S., Usmani, O.S., Zhang, Q., Ahmed, H., Allen, D., Ballereau, S., Batuwitage, M.K., Bedding, A., Behndig, A.F., Berglind, A., Berton, A., Bigler, J., Boedigheimer, M.J., Bønnelykke, K., Brinkman, P., Bush, A., Campagna, D., Casaulta, C., Chaiboonchoe, A., Davison, T., De Meulder, B., Delin, I., Dennison, P., Dodson, P., El Hadjam, L., Erzen, D., Faulenbach, C., Fichtner, K., Fitch, N., Formaggio, E., Gahlemann, M., Galffy, G., Garissi, D., Garret, T., Guillmant-Farry, E., Henriksson, E., Hoda, U., Hohlfeld, J.M., Hu, X., James, A., Johnson, K., Jullian, N., Kerry, G., Klüglich, M., Knowles, R., Konradsen, J.R., Kretsos, K., Krueger, L., Lantz, A-S., Larminie, C., Latzin, P., Lefaudeux, D., Lemonnier, N., Lowe, L.A., Lutter, R., Manta, A., Mazein, A., McEvoy, L., Menzies-Gow, A., Mores, N., Murray, C.S., Nething, K., Nihlén, U., Niven, R., Nordlund, B., Nsubuga, S., Pellet, J., Pison, C., Praticò, G., Puig Valls, M., Riemann, K., Rocha, J.P., Rossios, C., Santini, G., Sagi, M., Scott, S., Sehgal, N., Selby, A., Söderman, P., Sogbesan, A., Spycher, F., Stephan, S., Stokholm, J., Sunther, M., Szentkereszty, M., Tamasi, L., Tariq, K., Valente, S, Van Aalderen, W.M., Van Drunen, C.M., Van Eyll, J., Vyas, A., Yu, W., Zetterguist, W., Zolkipli, Z., Zwinderman, A.H., Agusti, A., Wedzicha, J.A., Donaldson, G.C., Faner, R., Breyer-Kohansal, R., Maitland-van der Zee, A.H., Melén, E., Allinson, J.P., Vanfleteren, L.E.G.W., Vestbo, J., Adcock, I.M., Lahousse, L., Van den Berge, M., Alter, P., Barbe, F., Brightling, C.E., Breyer, M.K., Burghuber, O.C., Casas, M., Chung, K.F., Cosío, B.G., Crispi, F., De Batlle, J., Fitting, J.W., Garcia, J., Hallberg, J., Hartl, S., Jarvis, D., Mathioudakis, A., Nicod, L., Papi, A., Ritchie, A., Sigsgaard, T., Sterk, P.J., Ullman, A., Vellvé, K., Vogelmeier, C., Wheelock, A.M., Wheelock, C.E., Kole, Tessa M *, Vanden Berghe, Elise, Kraft, Monica, Vonk, Judith M, Nawijn, Martijn C, Siddiqui, Salman, Sun, Kai, Fabbri, Leonardo M, Rabe, Klaus F, Chung, Kian Fan, Nicolini, Gabriele, Papi, Alberto, Brightling, Chris, Singh, Dave, van der Molen, Thys, Dahlén, Sven-Erik, Agusti, Alvar, Faner, Rosa, Wedzicha, Jadwiga A, Donaldson, Gavin C, Adcock, Ian M, Lahousse, Lies, Kerstjens, Huib A M, van den Berge, Maarten
Publikováno v:
In The Lancet Respiratory Medicine January 2023 11(1):55-64
This paper examines fundamental error characteristics for a general class of matrix completion problems, where the matrix of interest is a product of two a priori unknown matrices, one of which is sparse, and the observations are noisy. Our main cont
Externí odkaz:
http://arxiv.org/abs/1510.00701
Autor:
James AL; Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.; Medical School, The University of Western Australia, Perth, Western Australia, Australia., Caliskan G; Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy., Pesce G; Center for Research in Epidemiology and Population Health, INSERM, Paris-Saclay University, Paris-South University, UVSQ, Villejuif, France., Accordini S; Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy., Abramson MJ; School of Public Health & Preventive Medicine, Monash University, Melbourne, Australia., Bui D; Allergy and Lung Health Unit, School of Population and Global Health, The University of Melbourne, Melbourne, Australia., Musk AW; Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Perth, Western Australia, Australia.; School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia., Knuiman MW; School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia., Perret JL; Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia.; Institute for Breathing and Sleep (IBAS), Heidelberg, Melbourne, Australia., Jarvis D; National Heart and Lung Institute, Imperial College London, London, United Kingdom., Minelli C; National Heart and Lung Institute, Imperial College London, London, United Kingdom., Calciano L; Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy., Hui J; Department of Diagnostic Genomics, PathWest Laboratory Medicine, Perth, Western Australia, Australia.; Busselton Population Medical Research Institute, Busselton, Western Australia, Australia., Hunter M; School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia.; Busselton Population Medical Research Institute, Busselton, Western Australia, Australia., Thomas PS; Prince of Wales' Clinical School, UNSW, and Respiratory Medicine, Prince of Wales' Hospital, Randwick, New South Wales, Australia., Walters EH; School of Medicine, University of Tasmania, Hobart, Tasmania, Australia., Garcia-Aymerich J; ISGlobal, Barcelona, Spain.; Universitat Pompeu Fabra (UPF), Barcelona, Spain.; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain., Dharmage SC; Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia., Marcon A; Unit of Epidemiology and Medical Statistics, Department of Diagnostics and Public Health, University of Verona, Verona, Italy.
Publikováno v:
PloS one [PLoS One] 2024 Sep 19; Vol. 19 (9), pp. e0307386. Date of Electronic Publication: 2024 Sep 19 (Print Publication: 2024).
Publikováno v:
International Journal of COPD, Vol Volume 15, Pp 3079-3091 (2020)
Hannah R Whittaker,1 Jeanne M Pimenta,2 Deborah Jarvis,1 Steven J Kiddle,3 Jennifer K Quint1 1Respiratory Epidemiology, Occupational Medicine and Public Health, National Heart and Lung Institute, Imperial College London, London, UK; 2Epidemiology (Va
Externí odkaz:
https://doaj.org/article/86ed68bf2386481d8a419c4d9e95a559
Publikováno v:
In JSES International September 2020 4(3):584-586
This paper proposes a strategy for the detection and triangulation of structural anomalies in solid media. The method revolves around the construction of sparse representations of the medium's dynamic response, obtained by learning instructive dictio
Externí odkaz:
http://arxiv.org/abs/1405.2496
Autor:
Gonella, Stefano, Haupt, Jarvis D.
Publikováno v:
IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, v. 60, n.12, pp. 2553 - 2565
This work proposes an agnostic inference strategy for material diagnostics, conceived within the context of laser-based non-destructive evaluation methods, which extract information about structural anomalies from the analysis of acoustic wavefields
Externí odkaz:
http://arxiv.org/abs/1307.5102
Autor:
Rambhatla, Sirisha, Haupt, Jarvis D.
This work examines a semi-blind single-channel source separation problem. Our specific aim is to separate one source whose local structure is approximately known, from another a priori unspecified background source, given only a single linear combina
Externí odkaz:
http://arxiv.org/abs/1212.0451