Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Genetic Drift

Genetic Drift

Natural selection—probably the most well-known evolutionary mechanism—increases the prevalence of traits that enhance survival and reproduction. However, evolution does not merely propagate favorable traits, nor does it always benefit populations.

Diffusion

Diffusion

Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the...

Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

Passive Diffusion: Overview and Kinetics

Passive Diffusion: Overview and Kinetics

Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
When administered orally, drugs establish a substantial concentration gradient between the gastrointestinal (GI) lumen and the bloodstream, expediting...

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Generative diffusion models in infinite dimensions: a survey.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025

Same author

Multi-Modal Latent Diffusion.

Entropy (Basel, Switzerland)·2024

Same author

How Much Is Enough? A Study on Diffusion Times in Score-Based Generative Models.

Entropy (Basel, Switzerland)·2023

Same author

A Scalable Bayesian Sampling Method Based on Stochastic Gradient Descent Isotropization.

Entropy (Basel, Switzerland)·2021

Same author

Probabilistic Ensemble of Deep Information Networks.

Entropy (Basel, Switzerland)·2020

Same journal

Research on a Regional Availability Evaluation Model for Road-Area High-Entropy Energy Based on Synergy Factors.

Entropy (Basel, Switzerland)·2026

Same journal

Atmospheric Turbulence Channel Modeling and Performance Analysis of a CO-ZP-OFDM Coherent Optical Communication System for UAV Air-to-Ground Scenarios.

Entropy (Basel, Switzerland)·2026

Same journal

Information Geometry and Asymptotic Theory for SMML Estimators.

Entropy (Basel, Switzerland)·2026

Same journal

Correlation Entropy and Power-Law Kinetics.

Entropy (Basel, Switzerland)·2026

Same journal

Research on the Contagion of Systemic Financial Risk Under the Impact of Climate Risks-From the Perspective of Complex Networks and Machine Learning.

Entropy (Basel, Switzerland)·2026

Same journal

The Statistical-Mechanical Meaning of the Wave Function of Quantum Mechanics.

Entropy (Basel, Switzerland)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 10, 2025

3D Modeling of Dendritic Spines with Synaptic Plasticity

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

Latent Abstractions in Generative Diffusion Models.

Giulio Franzese¹, Mattia Martini², Giulio Corallo^1,3

¹Department of Data Science, EURECOM, 06410 Biot, France.

Entropy (Basel, Switzerland)

|April 26, 2025

Summary

This summary is machine-generated.

Diffusion models generate high-dimensional data using latent abstractions. Our new theory frames these models as nonlinear filters, revealing how hidden states guide observable outputs.

Keywords:

diffusion models information theory nonlinear filtering world modeling

More Related Videos

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Published on: April 18, 2017

The Diffusion of Passive Tracers in Laminar Shear Flow

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

Related Experiment Videos

Last Updated: May 10, 2025

3D Modeling of Dendritic Spines with Synaptic Plasticity

3D Modeling of Dendritic Spines with Synaptic Plasticity

Published on: May 18, 2020

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Published on: April 18, 2017

The Diffusion of Passive Tracers in Laminar Shear Flow

The Diffusion of Passive Tracers in Laminar Shear Flow

Published on: May 1, 2018

Area of Science:

Artificial Intelligence
Machine Learning
Information Theory

Background:

Diffusion models are powerful generative tools for high-dimensional data.
Understanding the internal mechanisms of diffusion models, particularly latent abstractions, is crucial.

Purpose of the Study:

To introduce a novel theoretical framework for understanding diffusion models.
To interpret Stochastic Differential Equation (SDE)-based generative models through the lens of Nonlinear Filtering (NLF).
To empirically validate the proposed theoretical framework.

Main Methods:

Developed a new theoretical framework extending Nonlinear Filtering (NLF).
Formulated joint (state and measurement) dynamics and an information-theoretic measure of state influence.
Conducted an empirical study to validate the theoretical findings.

Main Results:

Diffusion models can be interpreted as a system of SDE, functioning as a nonlinear filter.
Unobservable latent abstractions steer the dynamics of the observable measurement process.
Empirical evidence supports the emergence of latent abstractions at various generative stages.

Conclusions:

The proposed NLF-based framework offers a new perspective on SDE-based diffusion models.
Latent abstractions play a critical role in guiding the generative process.
The findings provide theoretical and empirical support for the interpretation of diffusion models as nonlinear filters.