Results 11 to 20 of about 5,303,417 (204)
syN-BEATS for robust pollutant forecasting in data-limited context. [PDF]
Environ Monit AssessAbstract This research introduces syN-BEATS, a novel ensemble deep learning model tailored for effective pollutant forecasting under conditions of limited data availability. Based on the N-BEATS architecture, syN-BEATS integrates various configurations with differing numbers of stacks and blocks, effectively combining weak and strong learning ...
Berman J +3 more
europepmc +3 more sources
Double-Hit Lymphoma: Practicing in a Data-Limited Setting. [PDF]
J Oncol Pract, 2016 In the article that accompanies this commentary, Staton and Cohen1 present a rational approach to the care of patients with double-hit lymphoma (DHL). The major issues faced in the care of these patients—use of intensive induction regimens, CNS prophylaxis, and transplantation—are all well addressed within the authors’ therapeutic recommendations ...
Herrera AF.
europepmc +4 more sources
Training Strategies for Radiology Deep Learning Models in Data-limited Scenarios. [PDF]
Radiol Artif Intell, 2021 Candemir S +3 more
europepmc +2 more sources
The State of Cardiovascular Genomics: Abundant Data, Limited Information. [PDF]
Rev Esp Cardiol (Engl Ed), 2017 Aslibekyan S, Ruiz-Narváez EA.
europepmc +4 more sources
BMJ Health & Care Informatics, 2022 Objective Clinical notes contain information that has not been documented elsewhere, including responses to treatment and clinical findings, which are crucial for predicting key outcomes in patients in acute care.
Jingqing Zhang +5 more
doaj +1 more source
Frontiers in Marine Science, 2021 Most of the methods developed for managing data-limited stocks have been designed for long-lived species and result in a poor performance when applied to short-lived fish due to their high interannual variability of stock size (IAV).
Sonia Sánchez-Maroño +3 more
doaj +1 more source
Biology, 2022 The spiny lobster Palinurus elephas has been intensively harvested across its range and is generally considered overfished, with global landings declining sharply from an average of 820 t in 1960–79 to 385 t in 2000–19.
Régis Santos +5 more
doaj +1 more source
Expectation Propagation in the Large Data Limit [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2017 SummaryExpectation propagation (EP) is a widely successful algorithm for variational inference. EP is an iterative algorithm used to approximate complicated distributions, typically to find a Gaussian approximation of posterior distributions. In many applications of this type, EP performs extremely well.
Dehaene, Guillaume, Barthelme, Simon
openaire +4 more sources
F1000Research, 2023 Background Globally, scientists now have the ability to generate a vast amount of high throughput biomedical data that carry critical information for important clinical and public health applications.
Marni Torkel +9 more
doaj +1 more source
GANDaLF: GAN for Data-Limited Fingerprinting
Proceedings on Privacy Enhancing Technologies, 2021 Abstract We introduce Generative Adversarial Networks for Data-Limited Fingerprinting (GANDaLF), a new deep-learning-based technique to perform Website Fingerprinting (WF) on Tor traffic. In contrast to most earlier work on deep-learning for WF, GANDaLF is intended to work with few training samples, and achieves this goal through the use
Se Eun Oh +4 more
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