搜索结果: 1-15 共查到“理学 neural networks”相关记录87条 . 查询时间(0.19 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Entropy-Dissipation Informed Neural Networks for McKean-Vlasov type PDEs
McKean-Vlasov型 偏微分方程 熵耗散 信息神经网络
2023/4/13
We extend the concept of self-consistency for the Fokker-Planck equation (FPE) [Shen et al., 2022] to the more general McKean-Vlasov equation (MVE). While FPE describes the macroscopic behavior of par...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Generalization of Graph Neural Networks and Graph Structural Learning for Robust Representation
图神经网络 泛化 图结构学习 鲁棒表示
2023/4/18
This report consists of two parts associated with graph neural networks: generalization and graph structural learning. We first study the Rademacher complexity of GNNs, as one of independent-algorithm...
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Convergence Thery of Deep Neural Networks: Arbitrary Activation Functions and Pooling
深度神经网络 激活函数 池化
2023/4/28
Deep neural networks, as a powerful system to represent high dimensional complex functions, play a key role in deep learning. Convergence of deep neural networks is a fundamental issue in building the...
Stanford scientists study Pavlovian conditioning in neural networks
Stanford scientists Pavlovian conditioning neural networks
2017/3/30
In the decades following the work by physiologist Ivan Pavlov and his famous salivating dogs, scientists have discovered how molecules and cells in the brain learn to associate two stimuli, like Pavlo...
SPATIAL DATA MINING TOOLBOX FOR MAPPING SUITABILITY OF LANDFILL SITES USING NEURAL NETWORKS
Spatial data mining GIS neural networks ArcGIS toolbox landfill suitability analysis
2016/10/14
Mapping the suitability of landfill sites is a complex field and is involved with multidiscipline. The purpose of this research is to create an ArcGIS spatial data mining toolbox for mapping the suita...
Long-term trends in f0 F2 over Grahamstown using Neural Networks
Solar activity magnetic activity
2015/9/25
Many authors have claimed to have found long-term trends in f0 F2 , or the lack thereof, for different stations. Such investigations usually involve gross assumptions about the variation of f0 F2 with...
Tectonic modeling of Konya-Beysehir Region (Turkey) using cellular neural networks
Cellular Neural Network (CNN) forward and inverse modeling tectonic modeling boundary analysis Central Turkey
2015/9/2
In this paper, to separate regional-residual anomaly maps and to detect borders of buried geological bodies, we
applied the Cellular Neural Network (CNN) approach to gravity and magnetic anomaly maps...
Using neural networks to study the geomagnetic field evolution
Geomagnetic Field Geomagnetic Observatory Neural Networks (NN) time series time prediction
2015/9/1
study their time evolution in years. In order to find the best NN for the time predictions, we tested many different
kinds of NN and different ways of their training, when the inputs and targets are ...
How training and testing histories affect generalization:a test of simple neural networks
animal behaviour neural networks range effects generalization
2015/7/29
We show that a simple network model of associative learning can reproduce three findings that arise from particular training and testing procedures in generalization experiments: the effect of 1) ``er...
Neural networks have seen an explosion of interest over the last few years, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicin...
Convergence and Rate Analysis of Neural Networks for Sparse Approximation
Locally Competitive Algorithm sparse approximation global stability exponential convergence non-smooth objective
2011/9/23
Abstract: We present an analysis of the Locally Competitive Algorithm (LCA), a Hopfield-style neural network that solves sparse approximation problems (e.g., approximating a vector from a dictionary u...
Two-Photon Exchange Effect Studied with Neural Networks
proton form-factors two-photon exchange correction
2011/7/21
The novel approach to the extraction of the two-photon exchange (TPE) correction from the elastic $ep$ scattering data is presented. The Bayesian framework for the neural networks is adapted.
Thermal and Mechanical Modeling of Fluid and Heat Flow in a Porous Metal Using Neural Networks for Application as TPS in Space Vehicles
Neyral Network Porous Media Prous Passages
2013/1/30
This paper contains novel model using feedback neural networks for a work piece temperature predic- tion.The heat and mass transfer in a porous metal workpiece which is heated by a fire gun is studied...
Two-Photon Exchange Effect Studied with Neural Networks
Two-Photon Exchange Neural Networks
2011/7/21
The novel approach to the extraction of the two-photon exchange (TPE) correction from the elastic $ep$ scattering data is presented. The Bayesian framework for the neural networks is adapted. As the r...
Exponential stability of stochastic fuzzy Hopfield neural networks with time-varying delays and impulses
Stochastic Fuzzy Hopfield neural networks
2010/9/20
In this paper, the model of stochastic fuzzy Hopfield neural networks with time-varying delays and impulses (ISFVDHNNs) is established as a modified Takagi-Sugeno (TS) fuzzy model in which the consequ...