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DP2PNet: Diffusion-Based Point-to-Polygon Conversion for Single-Point Supervised Oriented Object Detection. [PDF]
Li P, Zhang L, Qu T.
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Inertia mechanisms in networks and knowledge diffusion in team inertia networks. [PDF]
Zhang P, Du H, Cheng Y, He X.
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Composite material surface microscopic defect detection and classification combining diffusion models and zero-shot learning. [PDF]
Fan W.
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Experimental study on concentration and temperature fields of carbon dioxide leakage under different terrain conditions. [PDF]
Li Y +6 more
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Constraint Decoupled Latent Diffusion for Protein Backmapping. [PDF]
Han X +5 more
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Multi stage generative upscaler recovers low resolution football broadcast images through diffusion models with ControlNet conditioning and LoRA fine tuning. [PDF]
Martini L +4 more
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Siberian Mathematical Journal, 2003
The author studies the elliptic system of first-order strongly nonlinear differential equations of one complex variable \[ u_{\bar z} = \mu^1u_z + \mu^2\bar u_{\bar z} + f \equiv A(z,u,v),\quad v = u_{z} \] which is commonly used to describe diffusion and convective processes of heat and mass transfer in a fluid.
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The author studies the elliptic system of first-order strongly nonlinear differential equations of one complex variable \[ u_{\bar z} = \mu^1u_z + \mu^2\bar u_{\bar z} + f \equiv A(z,u,v),\quad v = u_{z} \] which is commonly used to describe diffusion and convective processes of heat and mass transfer in a fluid.
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2001
Abstract Write down Bartlett’s equation in the case of the Wiener process D having drift m and instantaneous variance 1, and solve it subject to the boundary condition D(0) = 0.
Geoffrey R Grimmett, David R Stirzaker
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Abstract Write down Bartlett’s equation in the case of the Wiener process D having drift m and instantaneous variance 1, and solve it subject to the boundary condition D(0) = 0.
Geoffrey R Grimmett, David R Stirzaker
+4 more sources

