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Everything about Flow-based generative model
Statistical model used in machine learning
A flow-based generative model is a generative model used in machine learning that explicitly models a probability distribution by leveraging normalizing flow, which is a statistical method using the change-of-variable law of probabilities to transform a simple distribution into a complex one. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Flow-based generative modelA 5-minute orientation
- Skim a recent paper: Kullback-Leibler Divergence-Based Out-of-Distribution Detection With Flow-Based Generative ModelsInfluential work since 2022
- Pick up a classic book: Software EngineeringThe most-reprinted book on the subject
- Read the landmark paper: sEMG-Based Hand-Gesture Classification Using a Generative Flow ModelCited 31 times
- Go sideways: Jacobian matrix and determinantA closely related topic
- Go sideways: Implicit function theoremA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
sEMG-Based Hand-Gesture Classification Using a Generative Flow Model
CrystalFlow: a flow-based generative model for crystalline materials
Data augmentation on fault diagnosis of wind turbine gearboxes with an enhanced flow-based generative model
Flow-based Generative Emulation of Grids of Stellar Evolutionary Models
Human trajectory forecasting using a flow-based generative model
Neural Encoding and Decoding With a Flow-Based Invertible Generative Model
High-Dimensional Bayesian inference for model updating with neural likelihood approximator powered by dimensionality-reducing flow-based generative model
Flow-HBM: A generative likelihood-free hierarchical Bayesian model updating framework with dual normalizing flow-based inference networks
🆕 Influential since 2022
Kullback-Leibler Divergence-Based Out-of-Distribution Detection With Flow-Based Generative Models
Renormalization group flow, optimal transport, and diffusion-based generative model
A globally optimized fault diagnosis model based on generative flow model for imbalanced data
Generative geomodeling based on flow responses in latent space
Super-resolution of spin configurations based on flow-based generative models
📚 Books worth reading
Software EngineeringRoger S. Pressman, Bruce Maxim · 1982
Computer NetworksAndrew S. Tanenbaum, John David Wetherall · 1981
Neural Information ProcessingTingwen Huang · 2012
Clean CodeRobert C. Martin · 2008
The web application hacker's handbookDafydd Stuttard, Marcus Pinto · 2007
Software metricsNorman E. Fenton, Shari Lawrence Pfleeger · 1991- 📕Fluid-structure interactionJean-François Sigrist · 2015
Principles of water treatmentJohn C. Crittenden, Kerry J. Howe · 2012
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Jacobian matrix and determinant In vector calculus, the Jacobian matrix (/dʒəˈkoʊbiən/, /dʒɪ-, jɪ-/) of a vector-valued function of several variables is the matrix of all its first-order…
- Implicit function theorem In multivariable calculus, the implicit function theorem is a theorem that provides sufficient conditions under which a planar curve specified by F(x,y)=0…
- Calculus on Euclidean space In mathematics, calculus on Euclidean space is a generalization of calculus of functions in one or several variables to calculus of functions on Euclidean…
- Diffusion model In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable…
- Inverse function theorem In mathematical analysis, the inverse function theorem gives sufficient conditions for a function to have an inverse function. The essential idea is that…
- Dirichlet distribution In probability and statistics, the Dirichlet distribution (after Peter Gustav Lejeune Dirichlet), often denoted Dir(𝜶), is a family of continuous multivariate…
- Möbius transformation In geometry and complex analysis, a Möbius transformation of the complex plane is a rational function of the form f(z)=az+bcz+d of one complex variable…
- Determinant In mathematics, the determinant is a scalar-valued function of the entries of a square matrix that has many properties which make it fundamental for the…