- Referenced in 286 articles
- application to the problem of training neural networks. Scatter search is an evolutionary method that ... optimal weight values in a multilayer neural network. Through experimentation, we show that our instantiation...
- Referenced in 255 articles
- This package is for generating neural networks with many layers (deep architectures) and train them ... Reducing the dimensionality of data with neural networks” (G. E. Hinton, R. R. Salakhutdinov). This...
Neural Network Toolbox
- Referenced in 174 articles
- Neural Network Toolbox. Neural Network Toolbox™ provides functions and apps for modeling complex nonlinear systems ... modeled with a closed-form equation. Neural Network Toolbox supports supervised learning with feedforward, radial ... basis, and dynamic networks. It also supports unsupervised learning with self-organizing maps and competitive ... design, train, visualize, and simulate neural networks. You can use Neural Network Toolbox for applications...
- Referenced in 284 articles
- conducting machine learning and deep neural networks research, but the system is general enough...
- Referenced in 266 articles
- system implemented in the framework of adaptive networks. By using a hybrid learning procedure ... yielding remarkable results. Comparisons with artificial neural networks and earlier work on fuzzy modeling...
- Referenced in 148 articles
- PyTorch python package: Tensors and Dynamic neural networks in Python with strong GPU acceleration. PyTorch...
- Referenced in 105 articles
- link frequency assignment problem occurs when a network of radio links has to be established ... local search methods, genetic algorithms, neural networks, and potential reduction. These algorithms were tested...
- Referenced in 99 articles
- distance-based constructive learning algorithm Multi-layer networks of threshold logic units offer an attractive ... pattern classification systems. A new constructive neural network learning algorithm (DistAl) based on inter-pattern...
- Referenced in 94 articles
- Keras is a minimalist, highly modular neural networks library, written in Python and capable...
- Referenced in 60 articles
- Musicant, IEEE Trans. Neural Networks 10, 1032-1037 (1999)] and SMO [J. Platt, in: Advances...
- Referenced in 59 articles
- environment, but the tools in its neural networks toolbox for SOM were not really...
- Referenced in 21 articles
- Brian: a simulator for spiking neural networks in python. ”Brian” is a new simulator ... spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly...
- Referenced in 27 articles
- distributed pattern recognition codes in a neural network hierarchy is introduced. The search process functions...
- Referenced in 26 articles
- gotten from CRAN (www.cran.r-project.org). The rest -- neural networks, global and local Lyapunov exponents -- is here...
- Referenced in 25 articles
- design a novel type of neural network that directly consumes point clouds and well respects...
- Referenced in 24 articles
- human brain is a recurrent neural network (RNN): a network of neurons with feedback connections...
- Referenced in 17 articles
- linear search for sequence learning. Current Neural Network learning algorithms are limited in their ability ... systems. Most supervised gradient-based recurrent neural networks (RNNs) suffer from a vanishing error signal...
- Referenced in 22 articles
- trees, and even the use of neural networks in statistics. To demonstrate the interplay...
- Referenced in 13 articles
- BinaryConnect: Training Deep Neural Networks with binary weights during propagations. Deep Neural Networks (DNN) have ... components of the digital implementation of neural networks. We introduce BinaryConnect, a method which consists...
- Referenced in 15 articles
- architecture. A new type of cellular neural network is described, which may be classified ... broader category of generalized cellular neural networks (GCNN). Its novelty consists both in the task...