Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Niranjani Prasad"'
Autor:
Niranjani Prasad, Isabel Chien, Tim Regan, Angel Enrique, Jorge Palacios, Dessie Keegan, Usman Munir, Ryutaro Tanno, Hannah Richardson, Aditya Nori, Derek Richards, Gavin Doherty, Danielle Belgrave, Anja Thieme
Publikováno v:
PLoS ONE, Vol 18, Iss 11 (2023)
Externí odkaz:
https://doaj.org/article/3184a4a2a9254ff7bec5c1e02895eaca
Autor:
Niranjani Prasad, Aishwarya Mandyam, Corey Chivers, Michael Draugelis, C. William Hanson, Barbara E. Engelhardt, Krzysztof Laudanski
Publikováno v:
Journal of Personalized Medicine; Volume 12; Issue 5; Pages: 661
Both provider- and protocol-driven electrolyte replacement have been linked to the over-prescription of ubiquitous electrolytes. Here, we describe the development and retrospective validation of a data-driven clinical decision support tool that uses
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e397ec040a90e98c6f774060e90c3aca
https://doi.org/10.3390/jpm12050661
https://doi.org/10.3390/jpm12050661
Publikováno v:
CHIL
A key impediment to reinforcement learning (RL) in real applications with limited, batch data is in defining a reward function that reflects what we implicitly know about reasonable behaviour for a task and allows for robust off-policy evaluation. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d626b4d394af66e00f8c50d1a9635811
https://doi.org/10.1145/3368555.3384450
https://doi.org/10.1145/3368555.3384450
Publikováno v:
ICASSP
This paper investigates the scaling properties of Recurrent Neural Network Language Models (RNNLMs). We discuss how to train very large RNNs on GPUs and address the questions of how RNNLMs scale with respect to model size, training-set size, computat
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::674033605fc469613f340281a1cd9e8f
