Results 61 to 70 of about 1,029,862 (299)
Multi-view clustering by virtually passing mutually supervised smooth messages [PDF]
, 2022 While the existing multi-view affinity propagation (AP)-based clustering method inevitably works with more than one random initialization and parameter, a novel algorithm called MVCPMM is proposed from a new perspective to achieve more consistent multi ...
Chung, Fu Lai, Gu, Suhang, Wang, Shitong
core +1 more source
Modelling stem cell differentiation related processes—A practical overview for biologists
FEBS Letters, EarlyView.Stem cell differentiation is complex and difficult to control experimentally. This review introduces suitable computational modelling approaches that can support stem cell research, from mechanistic ODE and abstract models to multiscale and deep learning methods.
Ricco Zeegelaar +4 more
wiley +1 more source
View-Driven Multi-View Clustering via Contrastive Double-Learning
EntropyMulti-view clustering requires simultaneous attention to both consistency and the diversity of information between views. Deep learning techniques have shown impressive abilities to learn complex features when working with extensive datasets; however ...
Shengcheng Liu +4 more
doaj +1 more source
Multi-view positive and unlabeled learning [PDF]
, 2012 Learning with Positive and Unlabeled instances (PU learning) arises widely in information retrieval applications. To address the unavailability issue of negative instances, most existing PU learning approaches require to either identify a reliable set of
Tsang, IW +7 more
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Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Multi-View Graph Clustering by Adaptive Manifold Learning
Mathematics, 2022 Graph-oriented methods have been widely adopted in multi-view clustering because of their efficiency in learning heterogeneous relationships and complex structures hidden in data.
Peng Zhao, Hongjie Wu, Shudong Huang
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Semantically consistent multi-view representation learning
Knowledge-Based Systems, 2023 19 pages ...
Yiyang Zhou +3 more
openaire +2 more sources
Interpreting the effects of DNA polymerase variants at the structural level
Molecular Oncology, EarlyView.Using MAVISp and molecular dynamics simulations, we analyzed over 60 000 missense variants in POLE and POLD1 from ClinVar, COSMIC, cBioPortal, and saturation mutagenesis. Identified mechanistic indicators, including stability, binding, and long‐range, enable structural interpretation, providing ACMG‐like evidence for possible reclassification of VUS ...
Matteo Arnaudi +7 more
wiley +1 more source
Incremental Data Stream Classification with Adaptive Multi-Task Multi-View Learning
Big Data Mining and AnalyticsWith the enhancement of data collection capabilities, massive streaming data have been accumulated in numerous application scenarios. Specifically, the issue of classifying data streams based on mobile sensors can be formalized as a multi-task multi-view
Jun Wang +6 more
doaj +1 more source
Consensus Graph Learning for Multi-Task Multi-View Clustering [PDF]
Jisuanji gongchengMulti-view clustering focuses on mining consistency information between different views to improve performance. Most existing multi-view clustering algorithms focus on single-task multi-view clustering while ignoring the similarity of related tasks ...
WANG Lijuan, LI Xueyan, YIN Ming, HAO Zhifeng, CAI Ruichu, CHEN Wei, LIU Rui
doaj +1 more source