Results 41 to 50 of about 7,363,003 (254)
Task-Covariant Representations for Few-Shot Learning on Remote Sensing Images
Mathematics, 2023 In the regression and classification of remotely sensed images through meta-learning, techniques exploit task-invariant information to quickly adapt to new tasks with fewer gradient updates.
Liyi Zhang +3 more
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FEBS Letters, EarlyView.This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
Towards Meta-learning over Data Streams [PDF]
, 2014 Modern society produces vast streams of data. Many stream mining algorithms have been developed to capture general trends in these streams, and make predictions for future observations, but relatively little is known about which algorithms perform ...
Pfahringer, Bernhard +3 more
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IEEE AccessIntegrating knowledge across different domains is an essential feature of human learning. Learning paradigms such as transfer learning, meta-learning, and multi-task learning reflect the human learning process by exploiting the prior knowledge for new ...
Richa Upadhyay +3 more
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Molecular Oncology, EarlyView.This study shows that lung adenocarcinomas exploit developmental branching morphogenesis to acquire a therapy resistant basal‐like tumour cell state. This process was found to be regulated by combined TP53 loss‐of‐function and type‐I interferon signalling, identifying a novel axis for biomarker and therapeutic target discovery.
Kamila J Bienkowska +13 more
wiley +1 more source
EnergiesAccurate prediction of crude petroleum production in oil fields plays a crucial role in analyzing reservoir dynamics, formulating measures to increase production, and selecting ways to improve recovery factors.
Zhichao Xu, Gaoming Yu
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Meta-SE: A Meta-Learning Framework for Few-Shot Speech Enhancement
IEEE Access, 2021 Separating target speech from noisy signal is important for many realistic applications. Recently, deep neural network (DNN) has been widely used in speech enhancement (SE) and obtained prominent performance improvements. However, the current deep models
Weili Zhou, Mingliang Lu, Ruijie Ji
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Molecular Oncology, EarlyView.Single‐cell DNA methylation (scDNAme) profiling maps epimutational clonal evolution, revealing mechanisms of malignancy and therapeutic resistance across diverse cancer types. By providing a high‐resolution landscape of intratumoral heterogeneity, these technologies empower precise patient stratification, guide the development of enhanced ...
Ik Soo Kim
wiley +1 more source
Fairness-aware recommendation with meta learning
Scientific ReportsFairness has become a critical value online, and the latest studies consider it in many problems. In recommender systems, fairness is important since the visibility of items is controlled by systems.
Hyeji Oh, Chulyun Kim
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Leida xuebao, 2022 The sample scarcity issue is still challenged for SAR images interpretation. The number of geospatial targets related images is constrained of the SAR images interpretation ability of data acquisition, sample labeling, and the lack of target coverage ...
Yixuan LYU +7 more
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