HelioWebArtificial neural network
flowchart
AA["Associated Authors (69)"]
C[Artificial neural network]
BC["Broader Concepts (2)"]
NC["Narrower Concepts (58)"]
C== skos:broader ==>BC
NC== skos:broader ==>C
AA== dcterms:relation ==>C
click BC "#broader-concepts"
click NC "#narrower-concepts"
click AA "#associated-authors"
NI["add incoming edge"]
NO["add outgoing edge"]
NI-- ? -->C
C-- ? -->NO
click NI "#add-incoming-edge"
click NO "#add-outgoing-edge"
style NI stroke-width:2px,stroke-dasharray: 5 5
style NO stroke-width:2px,stroke-dasharray: 5 5
- Wikidata
- https://www.wikidata.org/wiki/Q192776
- OpenAlex ID
- https://openalex.org/C50644808 (API record)
- OpenAlex Description
- computational model used in machine learning, based on connected, hierarchical functions
- OpenAlex Level [?]
- 2
Broader Concepts
Narrower Concepts
- Activation function
- Adaptive resonance theory
- Artificial neuron
- Autoencoder
- Backpropagation
- Biological neuron model
- Boltzmann machine
- Cellular neural network
- Cerebellar model articulation controller
- Competitive learning
- Connectionism
- Content-addressable memory
- Convolution (computer science)
- Deep belief network
- Deep neural networks
- Digit recognition
- Early stopping
- Evolutionary robotics
- Extreme learning machine
- Feature recognition
- Feedforward neural network
- Function approximation
- Generalization error
- Gradient descent
- Hebbian theory
- Hopfield network
- Hybrid neural network
- Learning classifier system
- Learning rule
- Learning vector quantization
- Levenberg–Marquardt algorithm
- MNIST database
- Mean absolute percentage error
- Models of neural computation
- Multilayer perceptron
- Neuroevolution
- Neuromorphic engineering
- Neutral network
- Nonlinear autoregressive exogenous model
- Online machine learning
- Overfitting
- Perceptron
- Radial basis function
- Recurrent neural network
- Residual neural network
- Restricted Boltzmann machine
- Self-organizing map
- Sigmoid function
- Soft computing
- Softmax function
- Spiking neural network
- Stochastic computing
- Stochastic gradient descent
- Structural risk minimization
- Supervised learning
- Synaptic weight
- Time delay neural network
- Winner-take-all
Associated Authors
- Aleix Espuña Fontcuberta
- Alok Sharma
- Alqamah Sayeed
- Amir Mortazavigazar
- Antonios Mamalakis
- Armin Mehrabian
- Ashish Mishra
- B. M. Swiger
- Bahram Gharabaghi
- Baoxiang Pan
- Bo Peng
- Christopher Zerafa
- Daniel Civitarese
- Daniel Wrench
- David K. Richardson
- Diljit Dutta
- Ehsan Foroumandi
- Ehsan Haghighat
- Emily M Gordon
- Felicia Nurindrawati
- Gemma J. Anderson
- Haizhao Yang
- Hwan‐Jin Song
- Hwisong Kim
- Hyeon–Joon Kim
- Imme Ebert‐Uphoff
- Irina Zhelavskaya
- Jared Willard
- Jungbin Mok
- K. Ranjith
- Kamyar Azizzadenesheli
- Kathryn Lawson
- Kyongsik Yun
- Leena Khadke
- Lena Chang
- Linsey Passarella
- Louisa Barama
- M. Sobhi Alasta
- Majdi Fanous
- Majid Rasht‐Behesht
- Marvin Höge
- Md Abdullah Al Mehedi
- Mingliang Liu
- Mostafa Kiani Shahvandi
- Nathaniel H. Mathews
- Olya Skulovich
- Peishi Jiang
- Qianqian Liu
- Robert Chlumsky
- Sara Jamal
- Sarit Chanda
- Seoyoon Kwon
- Silvia Scarpetta
- Siyan Liu
- Sreenath Vemula
- Stefan Oehmcke
- Stephen G. Penny
- Tadd Bindas
- Takuya Kurihana
- Timothy C.C. Lui
- Tom Beucler
- Tse‐Chun Chen
- Umair bin Waheed
- Veeraraghavan Kannan
- William F. Jenkins
- Yajnaseni Dash
- Yang Chen
- Zachary M. Labe
- Zi Xian Leong
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