Search references for NETWORK BASED-DIFFUSION-ANALYSIS. Phrases containing NETWORK BASED-DIFFUSION-ANALYSIS
See searches and references containing NETWORK BASED-DIFFUSION-ANALYSIS!NETWORK BASED-DIFFUSION-ANALYSIS
Network-based diffusion analysis (NBDA) is a statistical tool to detect and quantify social transmission of information or a behaviour in social networks
Network-based diffusion analysis
Network-based_diffusion_analysis
Analysis of social structures using network and graph theory
Metcalfe's law Mosaic effect Netocracy Network-based diffusion analysis Network science Organizational network analysis Organizational patterns Small world phenomenon
Social_network_analysis
Technique for the generative modeling of a continuous probability distribution
In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable
Diffusion_model
Theory on how and why new ideas spread
recent diffusion research, even as the field has expanded into, and been influenced by, other methodological disciplines such as social network analysis and
Diffusion_of_innovations
Large baleen whale species
feeding has also been observed in solitary humpbacks. Using network-based diffusion analysis, one study argued that whales learned lobtailing from other
Humpback_whale
Image-generating machine learning model
Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology
Stable_Diffusion
Study of graphs as a representation of relations between discrete objects
sociology. Amongst many other applications, social network analysis has been used to understand the diffusion of innovations, news and rumors. Similarly, it
Network_theory
representation learning are based on diffusion maps and their extensions to handle multiple modalities. Multi-view diffusion maps address the challenge
Multimodal representation learning
Multimodal_representation_learning
Software which facilitates quantitative or qualitative analysis of social networks
Social network analysis (SNA) software is software which facilitates quantitative or qualitative analysis of social networks, by describing features of
Social network analysis software
Social_network_analysis_software
Type of convolutional neural network
convolutional neural network that was developed for image segmentation. The network is based on a fully convolutional neural network whose architecture
U-Net
Approach to decision-making and policy based on empirical data and analysis
Evidence-based policy (also known as evidence-informed policy or evidence-based governance) is a concept in public policy that advocates for policy decisions
Evidence-based_policy
Interdisciplinary field
segmentation: This method is based on the idea of evolution of segmentation function which is governed by an advection-diffusion model. To segment an object
Medical_image_computing
Academic field
sociology. Amongst many other applications, social network analysis has been used to understand the diffusion of innovation, news and rumors. Similarly, it
Network_science
Method of utilizing water in magnetic resonance imaging
development of DTI based tractography, a number of researchers pointed out a flaw in the diffusion tensor model. The tensor analysis assumes that there
Diffusion-weighted magnetic resonance imaging
Diffusion-weighted_magnetic_resonance_imaging
Type of machine learning model
replacing statistical phrase-based models with deep recurrent neural networks. These early NMT systems used LSTM-based encoder-decoder architectures
Large_language_model
Type of artificial neural network
method to train arbitrarily deep neural networks. It is based on layer by layer training through regression analysis. Superfluous hidden units are pruned
Feedforward_neural_network
Type of feedforward neural network
neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep learning network has
Convolutional_neural_network
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
Class of artificial neural network
updated at each time step based on the current input and the previous hidden state. This feedback mechanism allows the network to learn from past inputs
Recurrent_neural_network
Social structure made up of a set of social actors
network analysis to identify local and global patterns, locate influential entities, and examine dynamics of networks. For instance, social network analysis
Social_network
Machine learning technique
Meta-Pi network: building distributed knowledge representations for robust multisource pattern recognition" (PDF). IEEE Transactions on Pattern Analysis and
Mixture_of_experts
Deep learning method
learning. The core idea of a GAN is based on the "indirect" training through the discriminator, another neural network that can tell how "realistic" the
Generative adversarial network
Generative_adversarial_network
Subfield of machine learning
approaches: using (cyclic) networks with external or internal memory (model-based) learning effective distance metrics (metrics-based) explicitly optimizing
Meta-learning (computer science)
Meta-learning_(computer_science)
Large-scale brain network involved in detecting and attending to relevant stimuli
The network is detectable through independent component analysis of resting state fMRI images, as well as seed based functional connectivity analysis. The
Salience_network
Machine learning technique useful for dimensionality reduction
nodes and their arrangement are specified beforehand based on the larger goals of the analysis and exploration of the data. Each node in the map space
Self-organizing_map
Overview of and topical guide to machine learning
Constructing skill trees Decision tree learning Dehaene–Changeux model Diffusion map Dominance-based rough set approach Dynamic time warping Error-driven learning
Outline_of_machine_learning
Computational model used in machine learning
1971 paper described a deep network with eight layers trained by this method, training layer by layer via regression analysis. Superfluous hidden units
Neural network (machine learning)
Neural_network_(machine_learning)
Mathematical study of waiting lines, or queues
ISBN 978-0-7695-3360-5. S2CID 2714909. Chen, H.; Whitt, W. (1993). "Diffusion approximations for open queueing networks with service interruptions". Queueing Systems. 13
Queueing_theory
Theory of cultural learning in non-human animals
through social networks. These networks are currently being analyzed through computational methods such as network-based diffusion analysis (NBDA). In wild
Animal_culture
Properties of the operation of a secure cipher
In cryptography, confusion and diffusion are two properties of a secure cipher identified by Claude Shannon in his 1945 classified report A Mathematical
Confusion_and_diffusion
Signal processing computational method
potentially involving ICA-based analysis, have been used in real-world cyberespionage cases. In 2010, the FBI uncovered a Russian spy network known as the "Illegals
Independent component analysis
Independent_component_analysis
predominant architecture used by large language models such as GPT-4. Diffusion models were first described in 2015, and became the basis of image generation
History of artificial neural networks
History_of_artificial_neural_networks
Geometric algorithm
dimensionality reduction methods such as principal component analysis (PCA), diffusion maps are part of the family of nonlinear dimensionality reduction
Diffusion_map
Type of feedforward neural network
a multilayer perceptron (MLP) is a kind of modern feedforward neural network consisting of fully connected neurons with nonlinear activation functions
Multilayer_perceptron
Mathematical tool
Main path analysis is a mathematical tool, first proposed by Hummon and Doreian in 1989, to identify the major paths in a citation network, which is one
Main_path_analysis
Approach in data analysis
correlation-based (COP) and tensor-based outlier detection for high-dimensional data One-class support vector machines (OCSVM, SVDD) Replicator neural networks,
Anomaly_detection
reactions more closely, such as diffusion. One such diffusion model could conceivably consist of a transition function based on the average values of the
Continuous_automaton
Subset of artificial intelligence
Science Computer networks Computer vision Credit-card fraud detection Data quality DNA sequence classification Economics Financial data analysis General game
Machine_learning
learning framework for Java and C# supporting neural networks JOONE – Java-based neural network framework with modular architecture for learning tasks
Lists of open-source artificial intelligence software
Lists_of_open-source_artificial_intelligence_software
Recurrent neural network architecture
2026). "Forecasting Energy Consumption using Recurrent Neural Networks: A Comparative Analysis". arXiv:2601.17110 [cs.CY]. Calin, Ovidiu (14 February 2020)
Long_short-term_memory
area of social network analysis. Most of the early work in heterophily was done in the 1960s by Everett Rogers in his book Diffusion Of Innovations.
Heterophily
Statistics and machine learning technique
different ensemble learning approaches based on artificial neural networks, kernel principal component analysis (KPCA), decision trees with boosting, random
Ensemble_learning
Overview of and topical guide to deep learning
Diffusion model Energy-based model Generative adversarial network Mixture of experts Graph neural network Graph convolutional network Siamese network
Outline_of_deep_learning
tools. Particle based simulators treat each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane
List of systems biology modeling software
List_of_systems_biology_modeling_software
Theory within social science
constructionism, social shaping of technology, social network theory, normalization process theory, and diffusion of innovations theory are held to be important
Actor–network_theory
Religious conversion as sociological theory
Roman Empire as diffusion of innovation looks at religious change in the Roman Empire's first three centuries through the lens of diffusion of innovations
Christianization of the Roman Empire as diffusion of innovation
Christianization_of_the_Roman_Empire_as_diffusion_of_innovation
Method in natural language processing
include neural networks, dimensionality reduction on the word co-occurrence matrix, probabilistic models, explainable knowledge base method, and explicit
Word_embedding
Networks with multiple kinds of relations
real-world systems as multidimensional networks have yielded valuable insight in the fields of social network analysis, economics, urban and international
Multidimensional_network
Class of algorithms for pattern analysis
machine learning, kernel machines are a class of algorithms for pattern analysis, whose best known member is the support-vector machine (SVM). These methods
Kernel_method
Paradigm in machine learning that uses no classification labels
which can then be used as a module for other models, such as in a latent diffusion model. Tasks are often categorized as discriminative (recognition) or
Unsupervised_learning
Machine learning model for vision processing
synthesis, cluster analysis, autonomous driving. ViT had been used for image generation as backbones for GAN and for diffusion models (diffusion transformer
Vision_transformer
Ability of a computer system to cope with errors during execution
such as robust programming, robust machine learning, and Robust Security Network. Formal techniques, such as fuzz testing, are essential to showing robustness
Robustness_(computer_science)
Machine learning methods using multiple input modalities
Phenaki (2023), and Muse (2023). Unlike later models, DALL-E is not a diffusion model. Instead, it uses a decoder-only transformer that autoregressively
Multimodal_learning
Models used to produce word embeddings
Lukáš; Černocký, Jan; Khudanpur, Sanjeev (2010). "Recurrent Neural Network Based Language Model". Proceedings of Interspeech 2010. International Speech
Word2vec
Set of learning techniques in machine learning
NIPS. Coates, Adam; Lee, Honglak; Ng, Andrew Y. (2011). An analysis of single-layer networks in unsupervised feature learning (PDF). Int'l Conf. on AI
Feature_learning
Projection of data onto lower-dimensional manifolds
difference between diffusion maps and principal component analysis is that only local features of the data are considered in diffusion maps as opposed to
Nonlinear dimensionality reduction
Nonlinear_dimensionality_reduction
Genre of art
the 2020s, text-to-image models such as Midjourney, DALL-E and Stable Diffusion became widely available to the public, allowing users to quickly generate
AI_art
Deep learning library
second row (zero-based) # Output: tensor(0.5847) print(a.max()) # Output: tensor(0.8498) The following code block defines a neural network with linear layers
PyTorch
Reverse-engineering neural networks
while the broader field tended towards gradient-based approaches like saliency maps. Before circuit analysis, work in the subfield combined various techniques
Mechanistic_interpretability
Process of automating the application of machine learning
procedures Problem checking Leakage detection Misconfiguration detection Analysis of obtained results Creating user interfaces and visualizations There are
Automated_machine_learning
Smooth approximation of one-hot arg max
analysis, naive Bayes classifiers, and artificial neural networks. Specifically, in multinomial logistic regression and linear discriminant analysis,
Softmax_function
Statistical model used in machine learning
as variational autoencoders (VAEs), generative adversarial networks (GANs), or diffusion models, do not explicitly represent the likelihood function
Flow-based_generative_model
Statistical method in psychology
in the analysis. EFA procedures are more accurate when each factor is represented by multiple measured variables in the analysis. EFA is based on the
Exploratory_factor_analysis
Branch of machine learning
José Eduardo Ricciardi (2023-03-24). "Deep learning diffusion by search trend: a country-level analysis". Future Studies Research Journal: Trends and Strategies
Deep_learning
Flaw in mathematical modelling
In mathematical modeling, overfitting is the production of an analysis that corresponds too closely or exactly to a particular set of data and may therefore
Overfitting
System composed of many interacting components
applications for physics education research", finding that "framing a social network analysis within a complexity science perspective offers a new and powerful applicability
Complex_system
Algorithms for matrix decomposition
non-negative matrix approximation is a group of algorithms in multivariate analysis and linear algebra where a matrix V is factorized into (usually) two matrices
Non-negative matrix factorization
Non-negative_matrix_factorization
Machine learning technique
[available online] Pratt, L. Y. (1992). "Discriminability-based transfer between neural networks" (PDF). NIPS Conference: Advances in Neural Information
Transfer_learning
Method of modeling the metabolism of cells or microbes
reconstructions of metabolic networks. Genome-scale reconstructions describe all known or hypothesized biochemical reactions in an organism based on its entire genome
Flux_balance_analysis
Class of artificial neural network
gradient-based contrastive divergence algorithm. Restricted Boltzmann machines can also be used in deep learning networks. In particular, deep belief networks
Restricted_Boltzmann_machine
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
Density-based data clustering algorithm
Density-based spatial clustering of applications with noise (DBSCAN) is a data clustering algorithm proposed by Martin Ester, Hans-Peter Kriegel, Jörg
DBSCAN
Concept in sociology
manage information and are using micro-electronic based technologies." The diffusion of a networking logic substantially modifies the operation and outcomes
Network_society
Biology software
modeling the diffusion equation and reaction–diffusion of chemical fields, and biochemical transport, signaling, regulatory and metabolic networks solved with
CompuCell3D
Text-to-video model
faced by all current AI video diffusion models” and expected to improve with continued iteration. Like other diffusion-based video generators, LTX-2 can
LTX_(text-to-video_model)
Statistical model of language
been superseded by recurrent neural network–based models, which in turn have been superseded by Transformer-based models often referred to as large language
Language_model
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
Set of methods for supervised statistical learning
vector network is a supervised max-margin model with associated learning algorithms that analyze data for classification and regression analysis. Developed
Support_vector_machine
2026 multimodal model by OpenAI
software development; and the Spanish bank BBVA was using it for financial analysis. Other companies that OpenAI listed as having used GPT-5 pre-release include
GPT-5
A patient similarity network (PSN) is a mathematical model based on graph theory that allows for the visual and analytical exploration of complex relationships
Patient_similarity_network
Type of computational models
(2011). "Accounting for Diffusion in Agent Based Models of Reaction-Diffusion Systems with Application to Cytoskeletal Diffusion". PLOS ONE. 6 (9) e25306
Agent-based_model
Extracting features from raw data for machine learning
(2012), "Practical Recommendations for Gradient-Based Training of Deep Architectures", Neural Networks: Tricks of the Trade, Lecture Notes in Computer
Feature_engineering
Study of how patterns form by self-organization in nature
a filter called "KPT reaction". Reaction produced reaction–diffusion style patterns based on the supplied seed image. A similar effect to the KPT reaction
Pattern_formation
PDEs Von Neumann stability analysis — all Fourier components of the error should be stable Numerical diffusion — diffusion introduced by the numerical
List of numerical analysis topics
List_of_numerical_analysis_topics
Method of data analysis
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data
Principal_component_analysis
Parallel computing paradigm
Systems by Reaction-Diffusion Cellular Nonlinear Networks with Polynomial Weight-Functions", Int’l Workshop on Cellular Neural Networks and Their Applications
Cellular_neural_network
Optimization algorithm
Feature-based, Conditional Random Field Parsing. Proc. Annual Meeting of the ACL. LeCun, Yann A., et al. "Efficient backprop." Neural networks: Tricks
Stochastic_gradient_descent
Integrated circuit technology
asynchronous artificial neural network for efficient learning and inference. Also in 2017 IMEC’s self-learning chip, based on OxRAM, demonstrated music
Neuromorphic_computing
Process of reducing the number of random variables under consideration
Isomap, which uses geodesic distances in the data space; diffusion maps, which use diffusion distances in the data space; t-distributed stochastic neighbor
Dimensionality_reduction
Type of neural network which utilizes recursion
A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce
Recursive_neural_network
Artificial neural network that mimics neurons
performance than second-generation networks. Spike-based activation of SNNs is not differentiable, thus gradient descent-based backpropagation (BP) is not available
Spiking_neural_network
Framework for machine learning
and functional analysis. Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data. Statistical
Statistical_learning_theory
Increasing value with increasing participation
with the network effect, system dynamics can be used as a modelling method to describe the phenomena. Word of mouth and the Bass diffusion model are
Network_effect
Large-scale brain network active when not focusing on an external task
default mode network (DMN), also known as the default network, default state network, or anatomically the medial frontoparietal network (M-FPN), is a
Default_mode_network
Machine learning paradigm
Kramer, Mark A. (1991). "Nonlinear principal component analysis using autoassociative neural networks" (PDF). AIChE Journal. 37 (2): 233–243. Bibcode:1991AIChE
Self-supervised_learning
Problem-solving method
(2011) state that sub-sets of strategy include heuristics, regression analysis, and Bayesian inference. A heuristic is a strategy that ignores part of
Heuristic
Grouping a set of objects by similarity
subspace models when neural networks implement a form of Principal Component Analysis or Independent Component Analysis. A "clustering" is essentially
Cluster_analysis
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
Deficiency or inability to maintain one or more major components of identity
An identity disturbance or identity diffusion is an inability to maintain major components of identity. It refers to the fragmentation of one's self-image
Identity_disturbance
Machine-learning and computational-neuroscience conference
proposed in 1986 at the annual invitation-only Snowbird Meeting on Neural Networks for Computing organized by The California Institute of Technology and Bell
Conference on Neural Information Processing Systems
Conference_on_Neural_Information_Processing_Systems
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS
NETWORK BASED-DIFFUSION-ANALYSIS