Results 11 to 20 of about 9,085,112 (391)
Procedia Computer Science, 2023 Bayesian Neural Networks (BNNs) provide a tool to estimate the uncertainty of a neural network by considering a distribution over weights and sampling different models for each input. In this paper, we propose a method for uncertainty estimation in neural networks which, instead of considering a distribution over weights, samples outputs of each layer ...
Oleksiienko, Illia +2 more
openaire +4 more sources
International Journal of Advanced Robotic Systems, 2021 As a fundamental assumption in simultaneous localization and mapping, the static scenes hypothesis can be hardly fulfilled in applications of indoor/outdoor navigation or localization.
Yujia Zhai +4 more
doaj +1 more source
Frontiers in Genetics, 2022 Proteins need to interact with different ligands to perform their functions. Among the ligands, the metal ion is a major ligand. At present, the prediction of protein metal ion ligand binding residues is a challenge. In this study, we selected Zn2+, Cu2+,
Sixi Hao +13 more
doaj +1 more source
Frontiers in Genetics, 2022 The realization of many protein functions is inseparable from the interaction with ligands; in particular, the combination of protein and metal ion ligands performs an important biological function.
Shuang Xu +13 more
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DeepFM: A Factorization-Machine based Neural Network for CTR Prediction [PDF]
International Joint Conference on Artificial Intelligence, 2017 Learning sophisticated feature interactions behind user behaviors is critical in maximizing CTR for recommender systems. Despite great progress, existing methods seem to have a strong bias towards low- or high-order interactions, or require expertise ...
Huifeng Guo +4 more
semanticscholar +1 more source
Cells, 2022 The maladaptive response of the central nervous system (CNS) following nerve injury is primarily linked to the activation of glial cells (reactive gliosis) that produce an inflammatory reaction and a wide cellular morpho-structural and functional ...
Ciro De Luca +6 more
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EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces [PDF]
Journal of Neural Engineering, 2016 Objective. Brain–computer interfaces (BCI) enable direct communication with a computer, using neural activity as the control signal. This neural signal is generally chosen from a variety of well-studied electroencephalogram (EEG) signals. For a given BCI
Vernon J. Lawhern +5 more
semanticscholar +1 more source
Model migration neural network for predicting battery aging trajectories [PDF]
, 2020 Accurate prediction of batteries’ future degradation is a key solution to relief users’ anxiety on battery lifespan and electric vehicle’s driving range. Technical challenges arise from the highly nonlinear dynamics of battery aging.
Gao, Furong +5 more
core +1 more source
Thermodynamic Neural Network [PDF]
Entropy, 2020 A thermodynamically motivated neural network model is described that self-organizes to transport charge associated with internal and external potentials while in contact with a thermal reservoir. The model integrates techniques for rapid, large-scale, reversible, conservative equilibration of node states and slow, small-scale, irreversible, dissipative
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Energy-efficient control of pump units based on neural-network parameter observer [PDF]
, 2020 An observer based on an artificial neural network was designed. The observer determines the pumping unit performance depending on the operating point. Determination is based on the measured technological coordinates of the system and the pressure of the ...
Burian, S. O. +4 more
core +1 more source