Zobrazeno 1 - 10
of 5 973
pro vyhledávání: '"A, Lowman"'
SeeFar is an evolving collection of multi-resolution satellite images from public and commercial satellites. We specifically curated this dataset for training geospatial foundation models, unconstrained by satellite type. In recent years, advances in
Externí odkaz:
http://arxiv.org/abs/2406.06776
Autor:
Nicholas S. Marzolf, Michael J. Vlah, Heili E. Lowman, Weston M. Slaughter, Emily S. Bernhardt
Publikováno v:
Limnology and Oceanography Letters, Vol 9, Iss 5, Pp 524-531 (2024)
Abstract Modeling and sensor innovations in the last decade have enabled routine and continuous estimation of daily gross primary productivity (GPP) for rivers. Here, we generate and evaluate within and across year variability for 59 US rivers for wh
Externí odkaz:
https://doaj.org/article/761c705e89ff465d989a5cbb5b3afb2a
Autor:
Robert Motl, Whitney Neal, Deborah Backus, Jeffrey Hebert, Kevin McCully, Francois Bethoux, Prudence Plummer, Alexander Ng, John Lowman, Hollie Schmidt, Robert McBurney, Gary Cutter
Publikováno v:
BMC Neurology, Vol 24, Iss 1, Pp 1-8 (2024)
Abstract Background Multiple sclerosis (MS) is a leading cause of neurological disability among young and middle-aged adults worldwide, and disability is measured using a variety of approaches, including patient reported outcome measures (PROMs) such
Externí odkaz:
https://doaj.org/article/03669ce6a7b042faa5caacd85d9e9d5b
Publikováno v:
Journal of Managerial Psychology, 2024, Vol. 39, Issue 4, pp. 499-515.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JMP-05-2023-0275
Publikováno v:
Language, Speech & Hearing Services in Schools. Oct2024, Vol. 55 Issue 4, p1167-1178. 12p.
Publikováno v:
Hydrology and Earth System Sciences, Vol 28, Pp 1827-1851 (2024)
In recent years, extreme droughts in the United States have increased in frequency and severity, underlining a need to improve our understanding of vegetation resilience and adaptation. Flash droughts are extreme events marked by the rapid dry down o
Externí odkaz:
https://doaj.org/article/52f190502c4742728c765cf35190a3de
Publikováno v:
Scientific Data, Vol 11, Iss 1, Pp 1-22 (2024)
Abstract We present a novel data set for drought in the continental US (CONUS) built to enable computationally efficient spatio-temporal statistical and probabilistic models of drought. We converted drought data obtained from the widely-used US Droug
Externí odkaz:
https://doaj.org/article/f3aa3e8abf9049518164ea0abfc4e429
Training reinforcement learning agents that continually learn across multiple environments is a challenging problem. This is made more difficult by a lack of reproducible experiments and standard metrics for comparing different continual learning app
Externí odkaz:
http://arxiv.org/abs/2208.04287
Publikováno v:
International Journal of Physical Distribution & Logistics Management, 2024, Vol. 54, Issue 1, pp. 118-135.
Publikováno v:
In Journal of Research in Personality December 2024 113