Results 31 to 40 of about 953,953 (275)
A geometrical analysis of global stability in trained feedback networks [PDF]
, 2019 Recurrent neural networks have been extensively studied in the context of neuroscience and machine learning due to their ability to implement complex computations. While substantial progress in designing effective learning algorithms has been achieved in
Mastrogiuseppe, Francesca +1 more
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Identifying an efficient, thermally robust inorganic phosphor host via machine learning
Nature Communications, 2018 Identifying phosphors with good thermal stability and quantum efficiency is a prerequisite to improve the performance of white LED light sources. Here, a combined machine learning and density functional theory method is introduced to identify next ...
Ya Zhuo +4 more
doaj +1 more source
Mental models vs cell schemes [PDF]
Investigações em Ensino de Ciências, 2002 Student's mental representations of cell are examined from the perspectives of Johnson-Laird's mental models theory five years after instruction. The observed identity and stability of such representations are then interpreted under the framework of ...
Mª Luz Rodríguez Palmero +1 more
doaj
Molecular Oncology, EarlyView.Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee +8 more
wiley +1 more source
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Differential Privacy in Federated Learning: An Evolutionary Game Analysis
Applied SciencesThis paper examines federated learning, a decentralized machine learning paradigm, focusing on privacy challenges. We introduce differential privacy mechanisms to protect privacy and quantify their impact on global model performance.
Zhengwei Ni, Qi Zhou
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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
Learning Topology and Dynamics of Large Recurrent Neural Networks
, 2014 Large-scale recurrent networks have drawn increasing attention recently because of their capabilities in modeling a large variety of real-world phenomena and physical mechanisms.
He, Yuejia, She, Yiyuan, Wu, Dapeng
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Sparse and spurious: dictionary learning with noise and outliers [PDF]
, 2015 A popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictionary.
Bach, Francis +2 more
core +5 more sources
Lyapunov theory demonstrating a fundamental limit on the speed of systems consolidation
Physical Review ResearchThis article is part of the Physical Review Research collection titled Physics of Neuroscience. The nervous system reorganizes memories from an early site to a late site, a commonly observed feature of learning and memory systems known as systems ...
Alireza Alemi +2 more
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