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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 AI technology is the premier product
Stable_Diffusion
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
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
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
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
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
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
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
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)
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
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
Machine learning framework
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
Geometric algorithm
dimensionality reduction methods such as principal component analysis (PCA), diffusion maps are part of the family of nonlinear dimensionality reduction
Diffusion_map
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
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
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)
Type of machine learning model
Vibe, Gemini, Grok, Qwen and DeepSeek. LLMs are typically based on the transformer neural network architecture. Generative pre-trained transformers (GPTs)
Large_language_model
Type of feedforward neural network
non-convex with multiple local minima, theoretical analysis suggests that in sufficiently large networks, most local minima achieve error rates comparable
Multilayer_perceptron
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
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
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
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
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
Paradigm in machine learning that uses no classification labels
topographic map Meta-learning (computer science) Multivariate analysis Radial basis function network Weak supervision Wu, Wei. "Unsupervised Learning" (PDF)
Unsupervised_learning
Type of feedforward neural network
medical image analysis, natural language processing, brain–computer interfaces, and financial time series. Feedforward neural networks are usually fully
Convolutional_neural_network
Generative artificial intelligence 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_(world_model)
Computational model used in machine learning
neural networks are based on statistics developed over 200 years ago. The simplest kind of feedforward neural network (FNN) is a linear network, which
Neural network (machine learning)
Neural_network_(machine_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
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
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
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
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
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
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
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
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
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
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
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
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
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
Visual content generation through artificial intelligence
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
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
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
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
Machine learning model for vision processing
cluster analysis, autonomous driving, and radio map estimation. ViT had been used for image generation as backbones for GAN and for diffusion models (diffusion
Vision_transformer
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
Mathematical marketing model
The Bass model or Bass diffusion model was developed by Frank Bass. It consists of a simple differential equation that describes the process of how new
Bass_diffusion_model
Form of statistical factor analysis
confirmatory factor analysis is to test whether the data fit a hypothesized measurement model. This hypothesized model is based on theory and/or previous
Confirmatory_factor_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
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
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
Type of artificial neural network architecture
biomedical signal analysis, remote sensing, and environmental monitoring systems. Physics-informed RBF–KANs have been applied to transient diffusion interface
Kolmogorov–Arnold_Networks
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
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
Machine learning technique
[available online] Pratt, L. Y. (1992). "Discriminability-based transfer between neural networks" (PDF). NIPS Conference: Advances in Neural Information
Transfer_learning
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
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
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
Representation_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
Branch of machine learning
described a deep network with eight layers trained by this method, which is based on layer by layer training through regression analysis. Superfluous hidden
Deep_learning
Optimization algorithm for artificial neural networks
for training a neural network in computing parameter updates. It is an efficient application of the chain rule to neural networks. Backpropagation efficiently
Backpropagation
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
Subset of artificial intelligence
neural networks and reinforcement learning. In 2017, Ashish Vaswani and colleagues introduced the Transformer, a neural network architecture based primarily
Machine_learning
Machine learning technique
(November 1998). "A model of saliency-based visual attention for rapid scene analysis". IEEE Transactions on Pattern Analysis and Machine Intelligence. 20 (11):
Attention_(machine_learning)
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
Type of computational models
Social Network Analysis (SNA) tools and agent-based models are sometimes integrated, where the ABM is used to simulate the dynamics on the network while
Agent-based_model
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
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
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
Representation in natural language processing
through the usage of a siamese neural network architecture on the SNLI dataset. Other approaches are loosely based on the idea of distributional semantics
Sentence_embedding
American communication theorist and sociologist
an American communication theorist and sociologist, who originated the diffusion of innovations theory and introduced the term early adopter.[citation
Everett_Rogers
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
Software user interface
information provided by a system to determine the next course of action based on their judgment and experience. Intelligent systems can only go so far
Human-in-the-loop
Type of large language model
multimodal output, some generative transformer-based models are used for text-to-image technologies such as diffusion and parallel decoding. Such kinds of models
Generative pre-trained transformer
Generative_pre-trained_transformer
Operations researcher and applied probabilist
probabilist known for work on stochastic processing networks, queueing theory, and fluid and diffusion approximations. He is the Leon C. Welch Professor
Jim_Dai
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
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
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
Model-free reinforcement learning algorithm
it is a policy gradient method, often used for deep RL when the policy network is very large. The predecessor to PPO, Trust Region Policy Optimization
Proximal_policy_optimization
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
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
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
Concept in machine learning
various methods, focusing on performance analysis, feature examination, data auditing, and model behavior analysis. Performance-wise, unusually high accuracy
Leakage_(machine_learning)
Simulation of the sense of smell
proximity to the source.[further explanation needed] Another method based on the diffusion model is the hex-path algorithm, developed by R. Andrew Russel for
Machine_olfaction
Process of forming order by local interactions
self-assembly, molecular self-assembly, reaction–diffusion systems and oscillating reactions, autocatalytic networks, liquid crystals, grid complexes, colloidal
Self-organization
Class of artificial neural network
prohibited to make analysis tractable. On the other hand, the Stacked Boltzmann consists of a combination of an unsupervised three-layer network with symmetric
Restricted_Boltzmann_machine
Mathematical technique
mathematical analysis technique for locating the maxima of a density function, a so-called mode-seeking algorithm. Application domains include cluster analysis in
Mean_shift
Software program
Google engineer Alexander Mordvintsev that uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia, thus
DeepDream
System property to handle growing work
In computing, scalability is a characteristic of computers, networks, algorithms, networking protocols, programs and applications. An example is a search
Scalability
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
Automated recognition of patterns and regularities in data
research List of numerical-analysis software List of numerical libraries Neocognitron – Type of artificial neural network Perception – Interpretation
Pattern_recognition
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
Machine learning model training problem
processed by the network (the combination of unfolding and backpropagation is termed backpropagation through time). This section is based on the paper On
Vanishing_gradient_problem
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
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NETWORK BASED-DIFFUSION-ANALYSIS
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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
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