A gradient flow approach to quantization of measures

DOI10.1142/S0218202515500475zbMath1327.35197arXiv1412.8713MaRDI QIDQ5265468

Mikaela Iacobelli, Emanuele Caglioti, François Golse

Publication date: 28 July 2015

Published in: Mathematical Models and Methods in Applied Sciences (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1412.8713

zbMATH Keywords

gradient flowparabolic equationMonge-Kantorovich distancequantization of measures

Mathematics Subject Classification ID

Asymptotic behavior of solutions to PDEs (35B40) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Quasilinear parabolic equations with (p)-Laplacian (35K92) PDEs in connection with information and communication (35Q94) Quasilinear parabolic equations (35K59)

Related Items (5)

Quantization of probability distributions and gradient flows in space dimension 2 ⋮ Best finite constrained approximations of one-dimensional probabilities ⋮ A blob method for inhomogeneous diffusion with applications to multi-agent control and sampling ⋮ Variational methods for evolution. Abstracts from the workshop held November 12--18, 2017 ⋮ Weighted ultrafast diffusion equations: from well-posedness to long-time behaviour

Cites Work

• Unnamed Item
• Positivity, local smoothing, and Harnack inequalities for very fast diffusion equations
• Foundations of quantization for probability distributions
• Failure of the Strong Maximum Principle in Nonlinear Diffusion. Existence of Needles
• Nonlinear Differential Equations of Monotone Types in Banach Spaces

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