###### convolutional neural network

- After comparing different methods, long short-term memory (LSTM) and convolutional neural network (CNN) methods were selected as deep learning methods to classify Chinese text. (mdpi.com)
- Spatio-temporal chaotic dynamics in a two-dimensional excitable medium is (cross-) estimated using a machine learning method based on a convolutional neural network combined with a conditional random field. (frontiersin.org)
- This "black-box model" consists of a convolutional neural network (CNN) combined with a conditional random field (CRF) and will be introduced in section 2. (frontiersin.org)

###### training recurrent neural n

- Jaeger, H.: The "echo state" approach to analysing and training recurrent neural networks. (springer.com)

###### based on a recurrent

- First, you may want to create a robot controller based on a recurrent neural network, but get stuck at the training procedure. (dobots.nl)

###### IEEE Transactions on Neural Networks

- IEEE Transactions on Neural Networks , 11 (6), 1332-1346. (springer.com)
- IEEE Transactions on Neural Networks , 8 (5), 1156-1164. (springer.com)
- IEEE Transactions on Neural Networks , 13 (1), 101-116. (springer.com)
- IEEE Transactions on Neural Networks , 13 (6), 1364-1373. (springer.com)
- IEEE Transactions on Neural Networks , 16 (1), 10-23. (springer.com)
- IEEE Transactions on Neural Networks , 11 (3), 769-783. (springer.com)

###### Networks

- At the beginning of the 2000s, a specific type of Recurrent Neural Networks (RNNs) was developed with the name Echo State Network (ESN). (springer.com)
- Schmidhuber, J.: Deep learning in neural networks: an overview. (springer.com)
- Basterrech, S., Rubino, G.: Echo state queueing networks: a combination of reservoir computing and random neural networks. (springer.com)
- Manjunath, G., Jaeger, H.: Echo state property linked to an input: exploring a fundamental characteristic of recurrent neural networks. (springer.com)
- Neural Networks: Tricks of the Trade. (springer.com)
- Heart Sound Segmentation-An Event Detection Approach Using Deep Recurrent Neural Networks. (annals.org)
- A Three-Threshold Learning Rule Approaches the Maximal Capacity of Recurrent Neural Networks. (duke.edu)
- Bilski, J.: The UD RLS algorithm for training the feedforward neural networks. (springer.com)
- Bilski, J.: Parallel Structures for Feedforward and Dynamical Neural Networks (in Polish). (springer.com)
- Bilski, J., Smoląg, J.: Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks. (springer.com)
- Chu, J.L., Krzyźak, A.: The recognition of partially occluded objects with support vector machines, convolutional neural networks and deep belief networks. (springer.com)
- artificial neural networks (ANN) is one such method. (scielo.org.za)
- 7 proposed a new hybrid approach combining Elman's recurrent neural networks (ERNN) and ARIMA models. (scielo.org.za)
- Universal approximation theorem for interval neural networks. (springer.com)
- Are artificial neural networks black boxes? (springer.com)
- Interpretation of artificial neural networks by means of fuzzy rules. (springer.com)
- The extraction of Sugeno fuzzy rules from neural networks. (springer.com)
- In M. Verleysen (Ed.), Proceedings of the European Symposium on Artificial Neural Networks (pp. 49-54). (springer.com)
- Fuzzy perceptron neural networks for classifiers with numerical data and linguistic rules as inputs. (springer.com)
- Principal component analysis of fuzzy data using autoassociative neural networks. (springer.com)
- General fuzzy min-max neural networks for clustering and classification. (springer.com)
- ESNs are a type of recurrent neural network that is easier to train than conventional recurrent neural networks. (dobots.nl)
- In proceedings of the 15th European Symposium on Arti cial Neural Networks. (dobots.nl)
- Training large neural networks on massive datasets exposed significant parallelism that could be readily utilized by existing parallel chips such as GPUs. (forbes.com)
- Computer vision algorithms have a leg up in locality due to their heavy use of convolutional neural networks, but the recurrent neural networks used in speech and language applications will need some changes to improve locality, especially for inference. (forbes.com)
- Another possible direction is to merge ideas from convolutional and recurrent neural networks, but the best approach is yet to be seen. (forbes.com)
- In this paper, we provide a novel approach to the architectural design of deep Recurrent Neural Networks using signal frequency analysis. (bioportfolio.com)
- Distributed Newton Methods for Deep Neural Networks. (bioportfolio.com)
- The success of recent deep convolutional neural networks (CNNs) depends on learning hidden representations that can summarize the important factors of variation behind the data. (bioportfolio.com)
- Echo state networks (ESNs) are a novel approach to recurrent neural network training with the advantage of a very simple and linear learning algorithm. (mur.at)
- In this article echo state networks, a special form of recurrent neural networks, are discussed in the area of nonlinear audio signal processing. (mur.at)
- Echo state networks are a novel approach in recurrent neural networks with a very easy (linear) training algorithm. (mur.at)
- Learn about artificial neural networks and how they're being used for machine learning, as applied to speech and object recognition, image segmentation, modeling language and human motion, etc. (coursera.org)
- The students are expected to gain knowledge of state-of-the-art machine learning models such as recurrent neural networks, reservoir computing, deep learning, kernel methods and probabilistic generative models. (unipi.it)
- The first three parts introduce advanced models associated with three major machine learning paradigms, that are neural networks, probabilistic and Bayesian learning and kernel methods. (unipi.it)
- The connection with these and convolutional neural networks is suggestive for the same reason. (danmackinlay.name)
- Alex Graves Generating Sequences With Recurrent Neural Networks , generates handwriting. (danmackinlay.name)
- Charming connection with my other research into acoustics , what I would call "Gerzon allpass" filters are now hip for use neural networks because of favourable normalisation characteristics. (danmackinlay.name)
- Kalman fiters, but rebranded in the fine neural networks tradition of taking something uncontroversial from another field and putting the word "neural" in front. (danmackinlay.name)
- Neural Networks , 21(5), 786-795. (danmackinlay.name)

###### Reservoir

- The reservoir has two main parameters that impact the accuracy of the model: the reservoir size (number of neurons in the RNN) and the spectral radius of the hidden-hidden recurrent weight matrix. (springer.com)
- Instead, the recurrent neural network is used as a reservoir of non-linear combinations of the input data, and this reservoir is used to train a simple perceptron output node with regression. (dobots.nl)

###### artificial neural

- Recurrent quantum neural network (RQNN) is an artificial neural network model which can perform stochastic filtering without any prior knowledge of the signal and noise. (springer.com)

###### Algorithms

- At Baidu's Silicon Valley AI Lab, we are proactively trying several approaches to change our algorithms to harness the potential of locality, and early experiments show very promising signs of overcoming this challenge. (forbes.com)

###### computation

- Maass, W., Natschläger, T., Markram, H.: Real-time computing without stable states: a new framework for a neural computation based on perturbations. (springer.com)

###### LSTM

- LSTM is a special kind of recurrent neural network (RNN), which is capable of processing serialized information through its recurrent structure. (mdpi.com)

###### Neurons

- In a traditional recurrent neural network, during the gradient back-propagation phase, the gradient signal can end up being multiplied a large number of times (as many as the number of timesteps) by the weight matrix associated with the connections between the neurons of the recurrent hidden layer. (danmackinlay.name)

###### algorithm

- A parallel architecture of the Levenberg-Marquardt algorithm for training a feedforward neural network is presented. (springer.com)

###### spectral

- A neural network-based method for spectral distortion correction in photon counting x-ray CT. (duke.edu)

###### computational

- Therefore, to alleviate the problems associated with homology based traditional approaches, numerous computational intelligence techniques have been proposed in the recent past. (hindawi.com)
- Here, we review computational approaches determining the nanopore sequencing error rate. (springer.com)

###### Parallel

- Detailed parallel neural network structures are explicitely discussed. (springer.com)
- Bilski, J., Smoląg, J.: Parallel approach to learning of the recurrent Jordan neural network. (springer.com)
- This approach would be very parallel, but also inefficient, because you would probably end up sending different friends to pick up items that are right next to each other. (forbes.com)

###### state

- You can consider the dynamic state of a neural network to be a short term memory. (coursera.org)

###### models

- We will follow an incremental approach starting from the introduction of learning models for sequential data processing and showing how these can be extended to deal with more complex structured domains. (unipi.it)
- See Sequential Neural Models with Stochastic Layers . (danmackinlay.name)

###### tasks

- The data serving as basis for this synthetic approach have been obtained with chronic multisite recordings from the visual cortex of anesthetized cats and from monkeys trained to solve cognitive tasks. (frontiersin.org)

###### sequence

- Therefore the sequence similarity based approaches may not always be adequate for protein function prediction. (hindawi.com)

###### sequential

- Rule extraction from support vector machines: A sequential covering approach. (springer.com)

###### model

- The performance of this approach is demonstrated using the four variables of the Bueno-Orovio-Fenton-Cherry model describing electrical excitation waves in cardiac tissue. (frontiersin.org)
- Ratcliff, R., Tuerlinckx, F.: Estimating parameters of the diffusion model: Approaches to dealing with contaminant reaction times and parameter variability. (springer.com)
- The ability to model correlations between pairwise residues allows it to obtain a significant improvement over standard 1D based approaches. (biomedcentral.com)

###### paper

- In this paper we propose an approach to optimally group the signals. (iospress.com)
- In this paper, we investigate the use of machine learning approaches to automatically annotate metal-binding proteins on the whole-proteome scale. (biomedcentral.com)

###### means

- Rather than the commonly used sequencing-by-synthesis approach, nanopores directly sense DNA or RNA bases by means of pores that are embedded in a membrane separating two compartments. (springer.com)

###### problem

- We present the effectiveness of this approach by applying it to an important problem in the railroadindustry, i.e., the inspection of railroad wheels. (iospress.com)
- In order to circumvent this problem, the recurrent connections are not trained at all in the ESN approach. (dobots.nl)

###### data

- Bratko and Suc 8 presented one approach to qualitative data mining, which aimed at finding qualitative patterns, or qualitative relationships, in numerical data. (scielo.org.za)

###### memory cell

- the rest of the recurrent neural network gets written into the memory cell. (coursera.org)
- A memory cell is composed of four main elements: an input gate, a neuron with a self-recurrent connection (a connection to itself), a forget gate and an output gate. (danmackinlay.name)

###### random

- This approach is effective because of the non-random nature of protein sequences, especially in regions such as catalytic domains. (biomedcentral.com)

###### unit

- Which again is a logistic unit controlled by the rest of the neural network. (coursera.org)

###### identification

- The proposed approach constitutes a highly automated tool for the identification of metalloproteins, which provides results of comparable quality with respect to highly manually refined predictions. (biomedcentral.com)