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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
Data diffusion machine (DDM) is a historical virtual shared memory architecture where data is free to migrate through the machine. Shared memory machines
Data_diffusion_machine
Image-generating machine learning model
donation from Stability and training data from non-profit organizations. Stable Diffusion is a latent diffusion model, a kind of deep generative artificial
Stable_Diffusion
Subset of artificial intelligence
previous machine learning approaches in performance. Statistics and mathematical optimisation methods compose the foundations of machine learning. Data mining
Machine_learning
Method of utilizing water in magnetic resonance imaging
the resulting data that uses the diffusion of water molecules to generate contrast in MR images. It allows the mapping of the diffusion process of molecules
Diffusion-weighted magnetic resonance imaging
Diffusion-weighted_magnetic_resonance_imaging
Research field that lies at the intersection of machine learning and computer security
fabricated data that violates the statistical assumption. Most common attacks in adversarial machine learning include evasion attacks, data poisoning attacks
Adversarial_machine_learning
Geometric algorithm
of a data set into Euclidean space (often low-dimensional) whose coordinates can be computed from the eigenvectors and eigenvalues of a diffusion operator
Diffusion_map
Process of analyzing large data sets
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics
Data_mining
Theory on how and why new ideas spread
Diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. The theory was popularized by Everett
Diffusion_of_innovations
Overview of and topical guide to machine learning
penalties. Applications of machine learning Bioinformatics Biomedical informatics Computer vision Customer relationship management Data mining Earth sciences
Outline_of_machine_learning
Set of methods for supervised statistical learning
vectors, developed in the support vector machines algorithm, to categorize unlabeled data.[citation needed] These data sets require unsupervised learning approaches
Support_vector_machine
Transport of dissolved species from the highest to the lowest concentration region
concept of diffusion is widely used in many fields, including physics (particle diffusion), chemistry, biology, sociology, economics, statistics, data science
Diffusion
Data analysis technique
copies of existing data. Synthetic Minority Over-sampling Technique (SMOTE) is a method used to address imbalanced datasets in machine learning. In such
Data_augmentation
Type of database that uses vectors to represent other data
audio, and other types of data, can all be vectorized. These feature vectors may be computed from the raw data using machine learning methods such as feature
Vector_database
Machine learning technique
November 2023). "DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models". NeurIPS 2023. arXiv:2305.16381. Retrieved 1 March 2024. Xu, Jiazheng;
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Machine learning model
human-drawn art. Text-to-image models are generally latent diffusion models, which perform the diffusion process in a compressed latent space rather than directly
Text-to-image_model
Diffusion model over latent embedding space
The Latent Diffusion Model (LDM) is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) group at LMU Munich. Introduced
Latent_diffusion_model
Tasks in machine learning
In machine learning, a common task is the study and construction of algorithms that can learn from and make predictions on data. Such algorithms function
Training, validation, and test data sets
Training,_validation,_and_test_data_sets
Flaw in mathematical modelling
the developers of some generative deep learning models such as Stable Diffusion and GitHub Copilot being sued for copyright infringement because these
Overfitting
Solution to a stochastic differential equation
processes are examples of diffusion processes. It is used heavily in statistical physics, statistical analysis, information theory, data science, neural networks
Diffusion_process
Partial differential equation describing the evolution of temperature in a region
"Scale-Space and Edge Detection Using Anisotropic Diffusion" (PDF), IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (7): 629–639, Bibcode:1990ITPAM
Heat_equation
Class of algorithms for pattern analysis
similarity function over all pairs of data points computed using inner products. The feature map in kernel machines is infinite dimensional but only requires
Kernel_method
AI that generates content
Grok and Qwen; text-to-image models such as DALL-E, Firefly, Stable Diffusion, and Midjourney; and text-to-video models such as Veo, LTX and Sora. Companies
Generative_AI
Type of large language model
transformer-based models are used for text-to-image technologies such as diffusion and parallel decoding. Such kinds of models can serve as visual foundation
Generative pre-trained transformer
Generative_pre-trained_transformer
semi-supervised machine-learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although
List of datasets for machine-learning research
List_of_datasets_for_machine-learning_research
Type of machine learning model
computational and data constraints of their time. In the early 1990s, IBM's statistical models pioneered word alignment techniques for machine translation,
Large_language_model
Topics referred to by the same term
software to control Dante-enabled Devices, see Dante (networking) Data Diffusion Machine, a virtual shared memory computer architecture from the 1990s Digital
DDM
Machine learning technique
In machine learning, normalization is a statistical technique with various applications. There are two main forms of normalization, namely data normalization
Normalization (machine learning)
Normalization_(machine_learning)
Concept in machine learning
In statistics and machine learning, leakage (also known as data leakage or target leakage) refers to the use of information during model training that
Leakage_(machine_learning)
Anime-focused imageboard website
platform, uses a custom version of the Stable Diffusion text-to-image diffusion model called NovelAI Diffusion, which is reported to be trained on a Danbooru
Danbooru
Machine learning methods using multiple input modalities
in E-commerce". arXiv:2112.11294 [cs.CV]. "Stable Diffusion Repository on GitHub". CompVis - Machine Vision and Learning Research Group, LMU Munich. 17
Multimodal_learning
Programmable machine that processes data
semiconductive surfaces for controlled diffusion", issued 13 August 1957 Archived 20 March 2025 at the Wayback Machine. Moskowitz, Sanford L. (2016). Advanced
Computer
Algorithm for modelling sequential data
generators like DALL-E (2021), Stable Diffusion 3 (2024), and Sora (2024), use transformers to analyse input data (like text prompts) by breaking it down
Transformer_(deep_learning)
Group of samples that have been tagged with one or more labels
After obtaining a labeled dataset, machine learning models can be applied to the data so that new unlabeled data can be presented to the model and a
Labeled_data
Machine learning strategy
case of machine learning in which a learning algorithm can interactively query a human user (or some other information source) to label new data points
Active learning (machine learning)
Active_learning_(machine_learning)
Optimization algorithm
Hluchý, Ladislav (19 January 2019). "Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey" (PDF). Artificial
Stochastic_gradient_descent
Technique to solve partial differential equations
problems in mathematical physics, such as conservative laws, diffusion process, advection-diffusion systems, and kinetic equations. Given noisy measurements
Physics-informed neural networks
Physics-informed_neural_networks
Automated recognition of patterns and regularities in data
based on patterns extracted from data. While similar, pattern recognition (PR) is not to be confused with pattern machines (PM) which may possess PR capabilities
Pattern_recognition
Process of automating the application of machine learning
search. In a typical machine learning application, practitioners have a set of input data points to be used for training. The raw data may not be in a form
Automated_machine_learning
Difficulties arising when analyzing data with many aspects ("dimensions")
dimension of the data. Dimensionally cursed phenomena occur in domains such as numerical analysis, sampling, combinatorics, machine learning, data mining and
Curse_of_dimensionality
Method of machine learning
In computer science, online machine learning is a method of machine learning in which data becomes available in a sequential order and is used to update
Online_machine_learning
Machine learning technique
with 15 billion parameters. MoE Transformer has also been applied for diffusion models. A series of large language models from Google used MoE. GShard
Mixture_of_experts
Type of convolutional neural network
U-Net architecture. The U-Net architecture has also been employed in diffusion models for iterative image denoising. This technology underlies many modern
U-Net
Neural network that learns efficient data encoding in an unsupervised manner
of data. Some of the most powerful AIs in the 2010s involved autoencoder modules as a component of larger AI systems, such as VAE in Stable Diffusion, discrete
Autoencoder
Machine learning model for vision processing
been used for image generation as backbones for GAN and for diffusion models (diffusion transformer, or DiT). DINO has been demonstrated to learn useful
Vision_transformer
Deep learning generative model to encode data representation
In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling in
Variational_autoencoder
Deep learning method
Realistic artificially generated media Deep learning – Branch of machine learning Diffusion model – Technique for the generative modeling of a continuous
Generative adversarial network
Generative_adversarial_network
Measurable property or characteristic
In machine learning and pattern recognition, a feature is an individual measurable property or characteristic of a data set. Choosing informative, discriminating
Feature_(machine_learning)
Approach in data analysis
remainder of that set of data. Anomaly detection finds application in many domains including cybersecurity, medicine, machine vision, statistics, neuroscience
Anomaly_detection
Machine learning paradigm
Self-supervised learning (SSL) is a paradigm in machine learning where a model is trained on a task using the data itself to generate supervisory signals, rather
Self-supervised_learning
Machine learning technique
gradient boosting in their machine-learned ranking engines. Gradient boosting is also utilized in High Energy Physics in data analysis. At the Large Hadron
Gradient_boosting
Extracting features from raw data for machine learning
engineering is a preprocessing step in supervised machine learning and statistical modeling which transforms raw data into a more effective set of inputs. Each
Feature_engineering
Paradigm in machine learning that uses no classification labels
a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data. Other frameworks
Unsupervised_learning
Properties of the operation of a secure cipher
output (ciphertext) by varying the application of the key to the data, while diffusion is hiding the plaintext statistics by spreading it over a larger
Confusion_and_diffusion
Type of feedforward neural network
activation functions, organized in layers, notable for being able to distinguish data that is not linearly separable. Modern neural networks are trained using
Multilayer_perceptron
AI that learns decision rules from data
"Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets". The Plant Cell. 23 (9): 3101–3116. Bibcode:2011PlanC
Rule-based_machine_learning
Statistical model used in machine learning
variational autoencoders (VAEs), generative adversarial networks (GANs), or diffusion models, do not explicitly represent the likelihood function. Let z 0 {\displaystyle
Flow-based_generative_model
Method of machine learning
In computer science, incremental learning is a method of machine learning in which input data is continuously used to extend the existing model's knowledge
Incremental_learning
Similarity measure for number sequences
In data analysis, cosine similarity is a measure of similarity between two non-zero vectors defined in an inner product space. Cosine similarity is the
Cosine_similarity
Recurrent neural network architecture
has wide applications in classification, data processing, time series analysis tasks, speech recognition, machine translation, speech activity detection
Long_short-term_memory
Homogenous cloud producer
air intended primarily to make light beams visible or create a subtle diffusion. Unlike theatrical fog, which is typically intended to be dense and/or
Haze_machine
Academic conference in machine learning
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year.
International Conference on Learning Representations
International_Conference_on_Learning_Representations
Property of a model
its predictions, and how well it can make predictions on previously unseen data that were not used to train the model. In general, as the number of tunable
Bias–variance_tradeoff
Method used to normalize the range of independent variables
data preprocessing step. Since the range of values of raw data varies widely, in some machine learning algorithms, objective functions will not work properly
Feature_scaling
Class of artificial neural network
recurrent neural networks (RNNs) are designed for processing sequential data, such as text, speech, and time series, where the order of elements is important
Recurrent_neural_network
Set of learning techniques in machine learning
feature detection or classification from raw data. This replaces manual feature engineering and allows a machine to both learn the features and use them to
Feature_learning
Intelligence of machines
Grok and Qwen; text-to-image models such as DALL-E, Firefly, Stable Diffusion, and Midjourney; and text-to-video models such as Veo, LTX and Sora. Companies
Artificial_intelligence
Early unclassified symmetric-key block cipher
The Data Encryption Standard (DES /ˌdiːˌiːˈɛs, dɛz/) is a symmetric-key algorithm for the encryption of digital data. Although its short key length of
Data_Encryption_Standard
Artificial intelligence research collective
5879544. "CLIP-Guided Diffusion". EleutherAI. Archived from the original on 29 August 2023. Retrieved 20 August 2023. "CLIP Guided Diffusion HQ 256x256.ipynb
EleutherAI
Conversational software
presented it more as a debunking exercise: In artificial intelligence, machines are made to behave in wondrous ways, often sufficient to dazzle even the
Chatbot
Vector quantization algorithm minimizing the sum of squared deviations
simplicity and computational efficiency. It was later adopted in early machine learning and data analysis tasks involving large datasets. Despite its widespread
K-means_clustering
Machine learning algorithm
learning is a supervised learning approach used in statistics, data mining and machine learning. In this formalism, a classification or regression decision
Decision_tree_learning
Machine learning technique
In machine learning, attention is a method that determines the importance of each component in a sequence relative to the other components in that sequence
Attention_(machine_learning)
Academic conference in machine learning
The International Conference on Machine Learning (ICML) is an international academic conference in machine learning held annually since 1980. It is the
International Conference on Machine Learning
International_Conference_on_Machine_Learning
Machine-learning and computational-neuroscience conference
Information Processing Systems (abbreviated as NeurIPS and formerly NIPS) is a machine learning and computational neuroscience conference held annually in December
Conference on Neural Information Processing Systems
Conference_on_Neural_Information_Processing_Systems
Field of machine learning
of Deep Reinforcement Learning to Policy Induction Attacks". Machine Learning and Data Mining in Pattern Recognition. Lecture Notes in Computer Science
Reinforcement_learning
Usage of artificial intelligence to generate music
machine application developed by researchers of the Instituto de Telecomunicações (Portugal) and University of Bern (Switzerland) that uses diffusion
Artificial intelligence in music
Artificial_intelligence_in_music
Ronen; Lo, Yu-Lun; Wu, Hau-Tieng (January 2019). "Alternating diffusion maps for multimodal data fusion". Information Fusion. 45: 346–360. doi:10.1016/j.inffus
Multimodal representation learning
Multimodal_representation_learning
Method in natural language processing
introduced through unaltered training data. Furthermore, word embeddings can even amplify these biases. Embedding (machine learning) Brown clustering
Word_embedding
Software user interface
decisions in building a model. HITL improves machine learning over random sampling by selecting the most critical data needed to refine the model. In simulation
Human-in-the-loop
Statistics and machine learning technique
stock market data and detect suspicious symptom of stock price manipulation. Implementation of ensemble learning not only with machine learning models
Ensemble_learning
Structuring text as input to generative artificial intelligence
depth-first, or beam. In 2022, text-to-image models like DALL-E 2, Stable Diffusion, and Midjourney were released to the public. These models take text prompts
Prompt_engineering
AI platform developed by IBM
training, validating, and deploying AI models; watsonx.data, a system for storing and managing data used by the models; and watsonx.governance, a toolkit
IBM_Watsonx
Models used to produce word embeddings
Google Groups. Retrieved 13 June 2016. "Visualizing Data using t-SNE" (PDF). Journal of Machine Learning Research, 2008, vol. 9, p. 2595. Retrieved 18
Word2vec
Framework for machine learning
statistical inference problem of finding a predictive function based on data. Statistical learning theory has led to successful applications in fields
Statistical_learning_theory
Chemical data page for water
This page provides supplementary data to the article properties of water. Further comprehensive authoritative data can be found at the NIST Chemistry
Water_(data_page)
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
Class of artificial neural networks
universal machine learning interatomic potentials (MLIPs) — models trained across diverse chemical domains rather than on system-specific data. Examples
Graph_neural_network
Deep learning architecture
the Structured State Space sequence (S4) model. To enable handling long data sequences, Mamba incorporates the Structured State Space sequence model (S4)
Mamba (deep learning architecture)
Mamba_(deep_learning_architecture)
Type of feedforward neural network
with Hadoop and Kafka. Dlib: A toolkit for making real world machine learning and data analysis applications in C++. Microsoft Cognitive Toolkit: A deep
Convolutional_neural_network
New technologies actively in development
"Does quantum mechanics offer the best way to protect our most valuable data?". The Independent. 31 March 2011. Archived from the original on 2 April
List_of_emerging_technologies
Electronic musical instrument that creates percussion sounds
integrated into Steinberg tools, and the diffusion-based DD-Shooter from Sonolisk. Programming of drum machines varies from product to product. On most
Drum_machine
Uranium processed to increase the percentage of uranium-235
which used gaseous diffusion and electromagnetic isotope separation to produce enriched uranium. Historically, gaseous diffusion and the gas centrifuge
Enriched_uranium
Deep learning library
by leveraging GPU resources. PyTorch utilises the tensor as a fundamental data type, similarly to NumPy. Training is facilitated by a reversed automatic
PyTorch
Academic journal
The Journal of Machine Learning Research is a peer-reviewed open access scientific journal covering machine learning. It was established in 2000 and the
Journal of Machine Learning Research
Journal_of_Machine_Learning_Research
Technique for the generative modeling of a discrete probability distribution
In machine learning, discrete diffusion models are a class of diffusion models, which themselves are a class of latent variable generative models. Each
Discrete_diffusion_model
Machine learning software library
their data centers for more than a year, and had found them to deliver an order of magnitude better-optimized performance per watt for machine learning
TensorFlow
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 Sander
DBSCAN
American manufacturer of sewing machines
Global Diffusion of the Sewing Machine, 1850–1914". Research in Economic History 20#1 (2001): 1–46. Godley, Andrew. "Selling the Sewing Machine Around
Singer_Corporation
Tree-based ensemble machine learning methods
are a popular method for various machine learning tasks. Tree learning is almost "an off-the-shelf procedure for data mining", say Hastie et al., "because
Random_forest
DATA DIFFUSION-MACHINE
DATA DIFFUSION-MACHINE
Female
Slavic
 Short form of Slavic Bogdana, DANA means "gift from God." Compare with other forms of Dana.
Boy/Male
Biblical
Diffusion; inclination; theft.
Female
Hindi/Indian
(लता) Hindi name derived from a plant name, from the Sanskrit word lata, LATA means "creeper," in reference to a creeping plant.
Female
Russian
 Short form of Russian Yekaterina, KATA means "pure." Compare with other forms of Kata.
Female
Hebrew
(דִּיתָה) Pet form of Hebrew Yehuwdiyth, DITA means "Jewess" or "praised." Compare with another form of Dita.
Female
Hungarian
 Short form of Hungarian Katalin, KATA means "pure." Compare with other forms of Kata.
Boy/Male
Biblical
Diffusion; inclination; theft.
Male
English
English surname transferred to unisex forename use, possibly DANA means "from Denmark."
Female
Polish
 Variant spelling of Polish Dyta, DITA means "rich battle." Compare with another form of Dita.
Male
Hebrew
(דֶּרַע) Hebrew name DARA means "the arm." In the bible, this is the name of a son of Zerah. Compare with other forms of Dara.
Female
English
 English surname transferred to unisex forename use, possibly DANA means "from Denmark." Compare with other forms of Dana.
Female
Hebrew
(×“Ö¼Ö¸× Ö¸×”) Feminine form of Hebrew Dan, DANA means "judge." Compare with other forms of Dana.
Female
Finnish
 Short form of Finnish Katariina, KATA means "pure." Compare with other forms of Kata.
Male
Iranian/Persian
 Short form of Persian Dârayavahush, DARA means "possesses a lot, wealthy." Compare with other forms of Dara.
Female
Finnish
Variant form of Finnish Aada, AATA means "noble."
Male
Turkish
Turkish name ATA means "ancestor."
Female
English
 Middle English name DARA means "brave, daring." Compare with another form of Dara.
Male
Irish
 From Irish Gaelic Mac Dara, DARA means "son of oak." Compare with other forms of Dara.
Male
Hebrew
Variant spelling of Hebrew Dathan, DATAN means "belonging to a fountain."
Female
Polish
Short form of Polish Edyta, DYTA means "rich battle."
DATA DIFFUSION-MACHINE
DATA DIFFUSION-MACHINE
Surname or Lastname
English (Oxfordshire) and Dutch
English (Oxfordshire) and Dutch : patronymic from Timm.
Surname or Lastname
English
English : variant of Kirkley.
Boy/Male
Hindu, Indian, Traditional
Summary
Boy/Male
Hebrew
Dog; brave. In the Old Testament, Caleb was a companion of Moses during his time in the wilderness.
Boy/Male
Hindu
Flag of victory
Girl/Female
Hindu
Goddess Durga
Boy/Male
Irish
From the Gaelic Maili which is a pet form of Mary 'bitter.
Boy/Male
Tamil
Like to think
Girl/Female
Arabic, Farsi, Iranian, Muslim
Lineage; Descendants of Holy Prophet (PBUH)
Boy/Male
Gujarati, Hindu, Indian, Kannada, Malayalam, Marathi, Oriya, Telugu
Lord Krishna
DATA DIFFUSION-MACHINE
DATA DIFFUSION-MACHINE
DATA DIFFUSION-MACHINE
DATA DIFFUSION-MACHINE
DATA DIFFUSION-MACHINE
n. pl.
See Datum.
n.
That addition to a writing, inscription, coin, etc., which specifies the time (as day, month, and year) when the writing or inscription was given, or executed, or made; as, the date of a letter, of a will, of a deed, of a coin. etc.
pl.
of Datum
a.
Having power to diffuse itself; diffusing itself.
a.
Having the quality of diffusing; capable of spreading every way by flowing; spreading widely; widely reaching; copious; diffuse.
n.
The point of time at which a transaction or event takes place, or is appointed to take place; a given point of time; epoch; as, the date of a battle.
adv.
In a diffusive manner.
n.
The fruit of the date palm; also, the date palm itself.
n.
The act of pouring out; as, effusion of water, of blood, of grace, of words, and the like.
n.
The emission and diffusion of rays of light.
v. t.
To note or fix the time of, as of an event; to give the date of; as, to date the building of the pyramids.
v. t.
The act of infusing, pouring in, or instilling; instillation; as, the infusion of good principles into the mind; the infusion of ardor or zeal.
n.
Prior date; a date antecedent to another which is the actual date.
v. t.
To note the time of writing or executing; to express in an instrument the time of its execution; as, to date a letter, a bond, a deed, or a charter.
n.
Infusion.
n.
Effusion; loss.
n.
One opposed to the diffusion of knowledge; an obscuriantist.
a.
Expansive; diffusive.
n.
The act of diffusing, or the state of being diffused; a spreading; extension; dissemination; circulation; dispersion.
n.
The act of passing by osmosis through animal membranes, as in the distribution of poisons, gases, etc., through the body. Unlike absorption, diffusion may go on after death, that is, after the blood ceases to circulate.