Results 61 to 70 of about 27,097 (268)
Advanced Science, EarlyView.ProMetNet introduces a biologically constrained deep learning framework for proteo‐metabolomic integration by embedding Reactome‐derived pathway topology into neural networks. It captures non‐linear molecular dependencies and pathway‐level metabolic reorganization, enabling interpretable discrimination.
Minghui Zhao +6 more
wiley +1 more source
Revista Tecnológica, 2014 La aplicación de modelos matemáticos en el manejo de cuencas hidrográficas tiene requerimientos exigentes de información y en su mayoría no han sido desarrollados para ser aplicados en regiones de montaña.
Jaime Eduardo Veintimilla +1 more
doaj
Advanced Science, EarlyView.Vision begins not with images but with change: the retina fires only when something moves, handing the brain a stream of spikes. A neuromorphic imaging system adopts the same strategy—an event sensor that sees like the retina, a spiking network that thinks like the brain—to track and reconstruct fully randomly moving targets through tissue (phantom ...
Ning Zhang, Arto Nurmikko
wiley +1 more source
A Novel Neuro-Fuzzy Model for Multivariate Time-Series Prediction
Data, 2018 Time series forecasting can be a complicated problem when the underlying process shows high degree of complex nonlinear behavior. In some domains, such as financial data, processing related time-series jointly can have significant benefits.
Alexander Vlasenko +3 more
doaj +1 more source
Regular Cycles of Forward and Backward Signal Propagation in Prefrontal Cortex and in Consciousness
Frontiers in Systems Neuroscience, 2016 This paper addresses two fundamental questions:(1) Is it possible to develop mathematical neural network models which can explain and replicate the way in which higher-order capabilities like intelligence, consciousness, optimization and prediction ...
Paul John Werbos +1 more
doaj +1 more source
High Voltage, 2021 This study presents a combined model based on the exploratory factor analysis (EFA) and the least square support vector machine (LSSVM) to predict the contamination degree of insulator surface. Firstly, EFA method is utilised to reduce numerous influence
Jiaxiang Sun +5 more
doaj +1 more source
Robust Implicit Backpropagation
CoRR, 2018 Arguably the biggest challenge in applying neural networks is tuning the hyperparameters, in particular the learning rate. The sensitivity to the learning rate is due to the reliance on backpropagation to train the network. In this paper we present the first application of Implicit Stochastic Gradient Descent (ISGD) to train neural networks, a method ...
Francois Fagan, Garud Iyengar
openaire +3 more sources
Backpropagation of accuracy [PDF]
Proceedings of International Conference on Neural Networks (ICNN'97), 2002 4 pages, 5 figures, The talk given on ICNN97 (The 1997 IEEE International Conference on Neural Networks, Houston, USA)
Masha Yu. Senashova +2 more
openaire +3 more sources
Advanced Science, EarlyView.A damage‐free iCVD fluoropolymer passivation strategy is introduced for ambipolar vertical OECTs. Vapor‐phase infiltration and thermal annealing induce nanoscale phase separation in the OMIEC channel, enhancing overall device performance. A single‐channel bipolar event‐driven spiking encoder is also demonstrated for electrocardiogram signal encoding ...
Junyeong Yang +7 more
wiley +1 more source
Advanced Science, EarlyView.A novel targeted and pH‐responsive MRI contrast agent was integrated with a 3D nnU‐Net deep learning framework to enable accurate delineation of tumor boundary morphology in HER2‐positive breast cancer imaging. ABSTRACT Breast cancer continues to be a leading cause of cancer‐related mortality in women globally, where precise diagnosis and clear tumor ...
Jiaying Zheng +7 more
wiley +1 more source