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Category of tailored neural networks
Spatial neural networks (SNNs) constitute a supercategory of tailored neural networks (NNs) for representing and predicting geographic phenomena. They
Spatial_neural_network
Type of feedforward neural network
A convolutional neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep
Convolutional_neural_network
Technique to solve partial differential equations
In machine learning, physics-informed neural networks (PINNs), also referred to as theory-trained neural networks (TTNs), are a type of universal function
Physics-informed neural networks
Physics-informed_neural_networks
Class of artificial neural networks
Graph neural networks (GNNs) are artificial neural networks designed for tasks whose inputs are graphs. Because graphs usually do not have a canonical
Graph_neural_network
Techniques to study geometric data
the geo-spatial datasets' variables depict non-linear relations. Examples of SNNs are the OSFA spatial neural networks, SVANNs and GWNNs. Spatial volatility
Spatial_analysis
Topics referred to by the same term
neural network, another term for an artificial neural network Spiking neural network, a type of artificial neural network Spatial neural network, another
SNN
Type of artificial neural network
machine learning, a neural field (also known as implicit neural representation, neural implicit, or coordinate-based neural network), is a mathematical
Neural_field
Class of artificial neural network
In artificial neural networks, recurrent neural networks (RNNs) are designed for processing sequential data, such as text, speech, and time series, where
Recurrent_neural_network
Classification of Artificial Neural Networks (ANNs)
Types of neural networks (NN) include a family of techniques. The simplest types have static components, including number of units, number of layers,
Types of artificial neural networks
Types_of_artificial_neural_networks
Network representing spatial objects
A spatial network (sometimes also geometric graph) is a graph in which the vertices or edges are spatial elements associated with geometric objects, i
Spatial_network
Branch of machine learning
machine learning, deep learning (DL) focuses on utilizing multilayered neural networks to perform tasks such as classification, regression, and representation
Deep_learning
Artificial neural networks (ANNs) are models created using machine learning to perform a number of tasks. While the computational implementations of ANNs
History of artificial neural networks
History_of_artificial_neural_networks
Physical implementation of an artificial neural network with optical components
An optical neural network is a physical implementation of an artificial neural network with optical components. Early optical neural networks used a photorefractive
Optical_neural_network
Hardware acceleration unit for artificial intelligence tasks
intelligence and machine learning applications, including artificial neural networks and computer vision. NPU can be standalone, a part of a CPU or a part
Neural_processing_unit
Machine learning framework
neural networks, marking a departure from the typical focus on learning mappings between finite-dimensional Euclidean spaces or finite sets. Neural operators
Neural_operators
Type of artificial neural network
A capsule neural network (CapsNet) is a machine learning system that is a type of artificial neural network (ANN) that can be used to better model hierarchical
Capsule_neural_network
Parallel computing paradigm
learning, Cellular Neural Networks (CNN) or Cellular Nonlinear Networks (CNN) are a parallel computing paradigm similar to neural networks, with the difference
Cellular_neural_network
Brainwaves, repetitive patterns of neural activity in the central nervous system
Neural oscillations, or brainwaves, are rhythmic or repetitive patterns of neural activity in the central nervous system. Neural tissue can generate oscillatory
Neural_oscillation
Type of activation function
In the context of artificial neural networks, the rectifier or ReLU (rectified linear unit) activation function is an activation function defined as the
Rectified_linear_unit
Neural network technology
In artificial neural networks, a convolutional layer is a type of network layer that applies a convolution operation to the input. Convolutional layers
Convolutional_layer
3D reconstruction technique
parametrized by a deep neural network (DNN). The network predicts a volume density and view-dependent emitted radiance given the spatial location ( x , y
Neural_radiance_field
the capacity to reason about spatial, translation-invariant properties is explicitly part of convolutional neural networks (CNN). The data to be considered
Relation_network
Distribution property in ecology
for integrating the spatial heterogeneity into spatial statistical models (e.g. spatial ensemble methods, spatial neural networks), so to improve their
Spatial_heterogeneity
Large-scale brain network active when not focusing on an external task
Gad A.; Spiers, Hugo J.; Arzy, Shahar (13 December 2023). "A neural circuit for spatial orientation derived from brain lesions". Cerebral Cortex. 34 (1)
Default_mode_network
Network or circuit of neurons
another to form large scale brain networks. Neural circuits have inspired the design of artificial neural networks, though there are significant differences
Neural_circuit
Topics referred to by the same term
Ecological network, a representation of interacting species in an ecosystem Neural network, a network or circuit of neurons Artificial neural network, a computing
Network
Machine learning technique
For convolutional neural networks, attention mechanisms can be distinguished by the dimension on which they operate, namely: spatial attention, channel
Attention_(machine_learning)
Array of processing elements specialized for parallelizable workloads
This choice stems from the fact that most works on spatial architectures focus on neural networks support and related optimizations. Note that a similar
Spatial_architecture
Type of reservoir computer
An echo state network (ESN) is a type of reservoir computer that uses a recurrent neural network with a sparsely connected hidden layer (with typically
Echo_state_network
Biological theory of intelligence
Convolutional neural network List of artificial intelligence projects Memory-prediction framework Multiple trace theory Neural history compressor Neural Turing
Hierarchical_temporal_memory
1943 paper proposing artificial neural networks
They considered neural networks that operate in discrete steps of time t = 0 , 1 , … {\displaystyle t=0,1,\dots } . The neural network contains a number
A Logical Calculus of the Ideas Immanent in Nervous Activity
A_Logical_Calculus_of_the_Ideas_Immanent_in_Nervous_Activity
2023.1168320. Attention Visual spatial attention Action Recognition Video content analysis Convolutional neural network Computer vision Center, UCF (2013-10-17)
Visual_temporal_attention
Hypothetical reconstruction of information from the brain
Neural decoding is a neuroscience field concerned with the hypothetical reconstruction of sensory and other stimuli from information that has already been
Neural_decoding
Type of convolutional neural network
a convolutional neural network that was developed for image segmentation. The network is based on a fully convolutional neural network whose architecture
U-Net
Correlation of brain activity across two or more people over time
Neural synchrony is the correlation of brain activity across two or more people over time. In social and affective neuroscience, neural synchrony specifically
Neural_synchrony
Concept in machine learning
express the convolution layers of a neural network. A convolutional layer has multiple inputs, each of which is a spatial structure such as an image or volume
Tensor_(machine_learning)
Architectural motif in neural networks for aggregating information
In neural networks, a pooling layer is a kind of network layer that downsamples and aggregates information that is dispersed among many vectors into fewer
Pooling_layer
Collections of brain regions working together
executive Cerebellar Spatial attention Language Lateral visual Temporal Visual perception/imagery Complex network Neural network (biology) Riedl, Valentin;
Large-scale_brain_network
Method by which information is represented in the brain
relationships among networks of neurons in an ensemble. Action potentials, which act as the primary carrier of information in biological neural networks, are generally
Neural_coding
Neural network architecture
Time delay neural network (TDNN) is a multilayer artificial neural network architecture whose purpose is to 1) classify patterns with shift-invariance
Time_delay_neural_network
Convolutional neural network structure
LeNet is a series of convolutional neural network architectures created by a research group at AT&T Bell Laboratories between of the period of 1988 to
LeNet
Research field in deep learning
Traditional deep learning models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), excel in processing data on regular grids
Topological_deep_learning
Form of artificial intelligence
intelligence that uses evolutionary algorithms to generate artificial neural networks (ANN), parameters, and rules. It is most commonly applied in artificial
Neuroevolution
Cell culture of neurons
Australia. Another example can be seen in the neurally controlled animat. The use of cultured neuronal networks as a model for their in vivo counterparts
Cultured_neuronal_network
Vertebrate brain region
"Hippocampome.org 2.0 is a knowledge base enabling data-driven spiking neural network simulations of rodent hippocampal circuits". eLife. 12 RP90597. doi:10
Hippocampus
Subset of artificial intelligence
explicitly programmed. Advances in the field of deep learning have allowed neural networks, a class of statistical algorithms, to surpass many previous machine
Machine_learning
Type of machine learning model
A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation
Large_language_model
Branch of neuroscience
cybernetics, quantitative psychology, machine learning, artificial neural networks, artificial intelligence and computational learning theory; although
Computational_neuroscience
Approach in generative models
new datasets with a similar distribution. Energy-based generative neural networks is a class of generative models, which aim to learn explicit probability
Energy-based_model
Kazakh mathematician (born 1953)
Spatial Neural Network for Recognition Problems with Binary Data" Dyusembaev A.E., "An approach to the solution of recognition problems using neural networks"
Anuar_Dyusembaev
Type of recurrent neural network with random and non-trainable internal structure
Reservoir computing is a framework for computation derived from recurrent neural network theory that maps input signals into higher dimensional computational
Reservoir_computing
AI's tendency to abruptly and drastically forget old info after learning new info
artificial neural network to abruptly and drastically forget previously learned information upon learning new information. Neural networks are an important
Catastrophic_interference
Phenomenon observed in the study of Artificial Neural Networks
study of artificial neural networks (ANNs), specifically deep neural networks (DNNs). It describes the tendency of deep neural networks to fit target functions
Frequency principle/spectral bias
Frequency_principle/spectral_bias
Study of graphs as a representation of relations between discrete objects
analysis. Many real networks are embedded in space. Examples include transportation and other infrastructure networks and brain neural networks. Several models
Network_theory
Large-scale brain network involved in voluntary orienting of attention
Abraham Z.; Sapir, Ayelet (November 2005). "Neural basis and recovery of spatial attention deficits in spatial neglect". Nature Neuroscience. 8 (11): 1603–1610
Dorsal_attention_network
Graph where most nodes are reachable in a small number of steps
connectomics and network neuroscience, have found the small-worldness of neural networks to be associated with efficient communication. In neural networks, short
Small-world_network
Computer scientist at Emory University
deep modeling, focusing on spatial, temporal, networked, textual, and heterogeneous types. He advanced new graph neural networks and inference strategies
Liang_Zhao
Topics referred to by the same term
Registered Clade Spatial-numerical association of response codes Stochastic Neural Analog Reinforcement Calculator, an early neural network implementation
SNARC
Ability of the brain to continuously change
Neuroplasticity, also known as neural plasticity or just plasticity, is the medium of neural networks in the brain to change through growth and reorganization
Neuroplasticity
AI that generates content
citation needed] World models are neural networks designed to learn representations of physical environments, including spatial and dynamic properties. Recent
Generative_AI
Phenomenon of the nervous system
Neural adaptation or sensory adaptation is a gradual decrease over time in the responsiveness of the sensory system to a constant stimulus. It is usually
Neural_adaptation
Technologies employing the World Wide Web to manage spatial data
List of GIS software Map database management Participatory GIS Spatial neural network Traditional knowledge GIS Fu, Pinde; Sun, Jiulin (2011). Web GIS:
Web_GIS
Algorithm for supervised learning of binary classifiers
instance. Spatially, the bias shifts the position (though not the orientation) of the planar decision boundary. In the context of neural networks, a perceptron
Perceptron
of convolutional neural network used to enhance a given image with no prior training data other than the image itself. A neural network is randomly initialized
Deep_image_prior
Approach in data analysis
advent of deep learning technologies, methods using Convolutional Neural Networks (CNNs) and Simple Recurrent Units (SRUs) have shown significant promise
Anomaly_detection
Patterns in both time and space
produces spatial patterns will also, due to the time-dependency of both reactions and diffusion, produce spatiotemporal patterns. Neural networks, both artificial
Spatiotemporal_pattern
German neuroscientist
neuroscientist. His research focuses on neural spiking patterns in neural networks, and their connection to learning, spatial representation and navigation. Since
Wulfram_Gerstner
Generating high-resolution video frames from given low-resolution ones
network) consists of spatial, temporal and reconstruction module. Spatial module composed of residual invertible blocks (RIB), which extract spatial features
Video_super-resolution
Subfield of artificial intelligence
Neuro-symbolic AI is a subfield of artificial intelligence that combines neural networks and symbolic AI approaches, such as knowledge representation and automated
Neuro-symbolic_AI
Intelligence of machines
space search and mathematical optimization, formal logic, artificial neural networks, and methods based on statistics, operations research, and economics
Artificial_intelligence
hemodynamic response is too slow to reflect a one-to-one correspondence with neural network dynamics, it is plausible that DFC is a reflection of the power of some
Dynamic functional connectivity
Dynamic_functional_connectivity
Network that allows computers to share resources and communicate with each other
as facilitated by networking hardware. Within a computer network, hosts are identified by network addresses, which allow networking hardware to locate
Computer_network
Delimited medium where some stimuli can evoke neuronal responses
context of artificial neural networks, most often in relation to convolutional neural networks (CNNs). So, in a neural network context, the receptive
Receptive_field
British neuroscientist
Neuroscience and Artificial Intelligence, and Editor-in-Chief of Network: Computation in Neural Systems published by Taylor & Francis. Stringer and his research
Simon_Stringer
Models of neural computation are attempts to elucidate, in an abstract and mathematical fashion, the core principles that underlie information processing
Models_of_neural_computation
American neurophysiologist and cybernetician (1898–1969)
The 1943 paper describes neural networks operating over time, and logical universals -- "there exists" and "for all"—for spatial objects, such as geometric
Warren_Sturgis_McCulloch
Field of technology that employs machine learning techniques
spatial. Historically in machine learning spatial data was analyzed using a convolutional neural network, and temporal data using a recurrent neural network
Document_AI
American-born computer scientist
spatial cliques by modeling the field potentials as a product of experts. Their formulation can be viewed as a shallow convolutional neural network.
Michael_J._Black
Gujarati government agency
solutions in implementing map-based GeoSpatial Information Systems. BISAG's SATCOM network is a satellite communication network service to provide distant interaction
Bhaskaracharya Institute For Space Applications and Geo-Informatics
Bhaskaracharya_Institute_For_Space_Applications_and_Geo-Informatics
Machine learning software library
for training interface and ArkTS programming interface for its NNRt (Neural Network Runtime) backend configurations via MindSpore Lite AI framework codebase
MindSpore
Competition of objects for visual processing
irrelevant information is ignored. The biasing from neural mechanisms guides the search to logical spatial locations (e.g. the table) and items that have similar
Biased_competition_theory
Branch of mathematical biology
attractors – neural integration: oculomotor control Ring attractors – neural integration: spatial orientation Plane attractors – neural integration: (higher
Dynamical_neuroscience
Type of neuron
arrangement of spatial firing fields, all at equal distances from their neighbors, led to a hypothesis that these cells encode a neural representation
Grid_cell
British neuroscientist (born 1966)
understanding memory and spatial cognition by developing computational models relating behaviour to activity in biological neural networks. Neil Burgess was
Neil_Burgess_(neuroscientist)
Cognitive process related to executive functions
in the neural systems for these different types of attention, and therefore research supporting both views is discussed below. Changes in spatial attention
Attentional_shift
Process in neuroscience
Summation, which includes both spatial summation and temporal summation, is the process that determines whether or not an action potential will be generated
Summation_(neurophysiology)
Study of the properties of codes and their fitness
efficient coding scheme for neural networks" (PDF). In Eckmiller, R.; Hartmann, G.; Hauske, G. (eds.). Parallel processing in neural systems and computers (PDF)
Coding_theory
Psychological focus, perception and prioritising discrete information
JM, Rao SM, Seidenberg M (October 2004). "Neural networks underlying endogenous and exogenous visual-spatial orienting". NeuroImage. 23 (2): 534–41. doi:10
Attention
Type of artificial intelligence system
learning, neural networks became dominant in image captioning. In 2015, methods emerged that used variations of convolutional neural networks (CNN) to
Vision–language_model
Network with non-trivial topological features
Small world networks Spatial network Trophic coherence B. S. Manoj, Abhishek Chakraborty, and Rahul Singh, Complex Networks: A Networking and Signal Processing
Complex_network
leveraging the powerful function approximation capabilities of deep neural networks, deep BSDE addresses the computational challenges faced by traditional
Deep backward stochastic differential equation method
Deep_backward_stochastic_differential_equation_method
Neuroscience theory of human intelligence
identify large-scale networks involved in cognition highlights the importance of multi-dimensional context in understanding the neural bases of cognitive
Parieto-frontal integration theory
Parieto-frontal_integration_theory
Topics referred to by the same term
spectrum, or otherwise discrete quantity Spatial quantization Charge quantization Quantization for LLMs (neural network weight optimization) Quantization (linguistics)
Quantization
Artificial intelligence researcher and writer
of neural network cookbook recipes written by Tom Brewe. AI Weirdness, Shane's blog on Artificial Intelligence, features everyday neural networks and
Janelle_Shane
Family of convolutional neural networks
Inception is a family of convolutional neural network (CNN) for computer vision, introduced by researchers at Google in 2014 as GoogLeNet (later renamed
Inception (deep learning architecture)
Inception_(deep_learning_architecture)
Geometric illusion with graphic implementations
"contour density" hypothesis, the number of zero crossings of the spatial profile of neural activity caused by the filled part of the Oppel–Kundt figure may
Oppel–Kundt_illusion
the spatial view cells constantly. This integration from various inputs develops continuous attractor networks. Continuous attractor neural networks, also
Spatial_view_cells
Algorithmic production of digital images
Convolutional Neural Networks". arXiv:1505.07376 [cs.CV]. Jetchev, Nikolay; Bergmann, Urs; Vollgraf, Roland (2016-11-24). "Texture Synthesis with Spatial Generative
Texture_synthesis
Form of homeostatic plasticity
Hebbian plasticity mechanisms modify neural synaptic connections selectively, synaptic scaling normalizes all neural synaptic connections by decreasing
Synaptic_scaling
Abstract machines which have a continuum of locations with finite states
similar patterns. Another important example is neural fields, which are the continuum limit of neural networks where average firing rates evolve based on
Continuous_spatial_automaton
SPATIAL NEURAL-NETWORK
SPATIAL NEURAL-NETWORK
Male
Scottish
Scottish Gaelic form of Greek Nikolaos, NEACAL means "victor of the people."
Boy/Male
Hindu
Cloud, Given by water
Girl/Female
English
The laurel tree or sweet bay tree symbolic of honor and victory.
Boy/Male
Hindu
New, Rainy, Handsome, Gratified
Boy/Male
Hindu
Lotus flower
Girl/Female
Hindu
Unique and different from all
Boy/Male
Arabic
Arab River
Girl/Female
Indian, Telugu
Crystal; Pure
Boy/Male
Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Punjabi, Sikh, Telugu
Protector
Boy/Male
Hindu
Without sound, Quiet, Silent
Girl/Female
Muslim
Royal
Girl/Female
Hindu
Crystal clear
Girl/Female
Arabic, Muslim
Royal
Girl/Female
Muslim/Islamic
The light e.g. nurul islam, the light of islam
Girl/Female
Hebrew
Light.
Biblical
treasurer of Nergal
Male
English
Variant spelling of English Neil, NEAL means "champion."
Female
Turkish
Turkish name NURAY means "bright moon."
Boy/Male
Biblical
Treasurer of Nergal.
Girl/Female
Hindu
There is no ending. ne-no tal-ending, The forehead
SPATIAL NEURAL-NETWORK
SPATIAL NEURAL-NETWORK
Girl/Female
Australian, French, Iranian, Parsi
A Female Character in Shahnameh
Surname or Lastname
English
English : from Middle English winyard ‘vineyard’, hence a topographic name for someone who lived by a vineyard, or a metonymic occupational name for someone who worked in one.Swedish : ornamental name formed with vin(d)- ‘wind’ + gard ‘farmhouse’, or a habitational name from a place so named.
Girl/Female
Indian
Glow of Moon, Light of the Moon
Boy/Male
Arabic
Grief; Distress
Boy/Male
Hindu, Indian, Punjabi, Sikh
Sweetness
Girl/Female
Hebrew
Graceful.
Boy/Male
Tamil
Boy/Male
Hindu
Boy/Male
Tamil
Boy/Male
Hindu, Indian
The Master of the Three Super Power Like Shiv Brahma and Vishnu
SPATIAL NEURAL-NETWORK
SPATIAL NEURAL-NETWORK
SPATIAL NEURAL-NETWORK
SPATIAL NEURAL-NETWORK
SPATIAL NEURAL-NETWORK
n.
Pertaining to a subordinate portion; as, a compound umbel is made up of a several partial umbels; a leaflet is often supported by a partial petiole.
a.
Limited in range; confined to a definite field of action, investigation, or discussion; as, a special dictionary of commercial terms; a special branch of study.
a.
Fixed or determined by nature; pertaining to the constitution of a thing; belonging to native character; according to nature; essential; characteristic; not artifical, foreign, assumed, put on, or acquired; as, the natural growth of animals or plants; the natural motion of a gravitating body; natural strength or disposition; the natural heat of the body; natural color.
adv.
Toward the neural side; -- opposed to haemad.
pl.
of Spatha
a.
Furnished with a spathe; as, spathal flowers.
a.
See Spatial.
a.
relating to the nerves or nervous system; taining to, situated in the region of, or on the side with, the neural, or cerebro-spinal, axis; -- opposed to hemal. As applied to vertebrates, neural is the same as dorsal; as applied to invertebrates it is usually the same as ventral. Cf. Hemal.
n.
Of, pertaining to, or affecting, a part only; not general or universal; not total or entire; as, a partial eclipse of the moon.
n.
One appointed for a special service or occasion.
a.
Resting; acting by mere weight without motion; as, statical pressure; static objects.
n.
A patrial noun. Thus Romanus, a Roman, and Troas, a woman of Troy, are patrial nouns, or patrials.
a.
Appropriate; designed for a particular purpose, occasion, or person; as, a special act of Parliament or of Congress; a special sermon.
n.
A person or a nation that takes no part in a contest between others; one who is neutral.
a.
Of or pertaining to feuds, fiefs, or feels; as, feudal rights or services; feudal tenures.
n.
The plural number; that form of a word which expresses or denotes more than one; a word in the plural form.
n.
Natural gifts, impulses, etc.
v. t.
To follow like a spaniel.
a.
Of or pertaining to the thigh or leg, or to any of the parts called crura; as, the crural arteries; crural arch; crural canal; crural ring.
pl.
of Neuron