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...id=18282872 |last1=Specht |first1=D. F. |title=A general regression neural network |s2cid=6266210 }}</ref> GRNN represents an improved technique in the neural networks based on the [[nonparametric regression]]. The idea is that every ...

{{Short description|Finding important subnetworks in neural networks}} ...its that sparse subnetworks can achieve comparable performance to the full network when trained in isolation from initialization. ...

{{short description|Type of neural network which utilizes recursion}} {{Distinguish|recurrent neural network}} ...

{{Short description|Architectural motif in neural networks for controlling information flow}} ...urrent neural network]]s (RNNs), but have also found applications in other architectures. ...

{{short description|Technique for training recurrent neural networks}} ...certain types of [[recurrent neural network]]s, such as [[Recurrent neural network#Elman networks and Jordan networks|Elman networks]]. The algorithm was inde ...

{{Short description|Series of convolutional neural networks for image classification}} *[[Convolutional neural network]] ...

...opens up new possibilities for analyzing, manipulating, and understanding neural networks at a fundamental level. This perspective allows researchers to app ...ese secondary models can be designed to predict properties of the original network, modify its behavior, or extract meaningful representations from its parame ...

{{Short description|THE LOTTERY TICKET HYPOTHESIS: FINDING SPARSE, TRAINABLE NEURAL NETWORKS}} ...1=Jonathan |title=The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks |date=2019-03-04 |eprint=1803.03635 |last2=Carbin |first2=Michael| ...

{{short description|Type of artificial neural network}} ...d on work done in my labs |url=https://people.idsia.ch/~juergen/most-cited-neural-nets.html |access-date=2022-04-30 |work=AI Blog |location=IDSIA, Switzerlan ...

{{Short description|Type of artificial neural network}} ...ively a class of [[deep learning|deep]] [[artificial neural network|neural network]], composed of multiple layers of [[latent variables]] ("hidden units"), wi ...

...s simply a real-valued function on the set of nodes of the graph. In graph neural networks, graph signals are sometimes called features. The signal space is == Algebraic Neural Networks == ...

{{Short description|Neural network working on two input vectors}} ...' (sometimes called a '''twin neural network''') is an [[artificial neural network]] that uses the same weights while working in tandem on two different input ...

...ibution over functions corresponding to an infinitely wide Bayesian neural network.}} ...iety of network architectures converges to a GP in [[Large width limits of neural networks|the infinitely wide limit]], [[convergence in distribution|in the ...

* [[Convolutional neural network]] ...eibtisch-mit-Objekten.jpg|thumb|Objects detected with OpenCV's Deep Neural Network module by using a YOLOv3 model trained on [[COCO (dataset)|COCO]] dataset c ...

{{Short description|Neural network technology}} ...ding blocks of [[convolutional neural networks]] (CNNs), a class of neural network most commonly applied to images, video, audio, and other data that have the ...

...aushik |last6=Stuart |first6=Andrew |last7=Anandkumar |first7=Anima |title=Neural operator: Learning maps between function spaces |journal=Journal of Machine ...=David A. |last4=Coenen |first4=Frans |last5=Ma |first5=Fei |title=Fourier Neural Operator for Fluid Flow in Small-Shape 2D Simulated Porous Media Dataset |j ...

{{short description|Artificial neural network architecture}} [[File:DNC training recall task.gif|thumb|300px|A differentiable neural computer being trained to store and recall dense binary numbers. Performanc ...

'''MobileNet''' is a family of [[convolutional neural network]] (CNN) architectures designed for [[image classification]], [[object detection]], and other comp ...|last1=Howard |first1=Andrew G. |title=MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications |date=2017-04-16 |arxiv=1704.04861 ...

{{short description|Memory unit used in neural networks}} ...hive.org/web/20211110112626/http://www.wildml.com/2015/10/recurrent-neural-network-tutorial-part-4-implementing-a-grulstm-rnn-with-python-and-theano/ |url-sta ...

{{short description|Family of convolutional neural networks}} *[[Convolutional neural network]] ...