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Gabriel Peyré

@gabrielpeyre • 102,535 subscribers

@CNRS researcher at @ENS_ULM. One tweet a day on computational mathematics.

Shorts

Mathematical modeling: part 1/2.

Mathematical modeling: part 1/2.

231,120 просмотров

Taylor series expansion of sine.

Taylor series expansion of sine.

305,048 просмотров

Fokker-Planck equation equivalently describes the movement of a random particle with a drift (as a stochastic ODE) and the evolution of its density (as a PDE).

Fokker-Planck equation equivalently describes the movement of a random particle with a drift (as a stochastic ODE) and the evolution of its density (as a PDE).

225,217 просмотров

Heat, Wave and Schrodinger equations are fundamental linear partial differential equations of physics.

Heat, Wave and Schrodinger equations are fundamental linear partial differential equations of physics.

232,236 просмотров

Comparison of the Wasserstein, Hellinger, Kullback-Leibler and reverse KL on the space of Gaussian distributions.

Comparison of the Wasserstein, Hellinger, Kullback-Leibler and reverse KL on the space of Gaussian distributions.

206,420 просмотров

Heat diffusion vs. wave equation on a surface.

Heat diffusion vs. wave equation on a surface.

205,129 просмотров

Lorenz attractor is the set of limit trajectories for a simplified mathematical model for atmospheric convection. It has a fractal geometry.

Lorenz attractor is the set of limit trajectories for a simplified mathematical model for atmospheric convection. It has a fractal geometry.

168,783 просмотров

Poljak heavy ball and Nesterov methods speed up gradient descent by introducing momentum. Corresponding to second order ODEs.

Poljak heavy ball and Nesterov methods speed up gradient descent by introducing momentum. Corresponding to second order ODEs.

141,154 просмотров

The marching squares/cubes is the standard algorithm to extract iso-curves/surfaces from a discretized image/volume.

The marching squares/cubes is the standard algorithm to extract iso-curves/surfaces from a discretized image/volume.

130,317 просмотров

Impact of the interpolation method on the level set of the resulting function.

Impact of the interpolation method on the level set of the resulting function.

125,323 просмотров

Oldies but goldies: L. Greengard and V. Rokhlin, A Fast Algorithm for Particle Simulations, 1987. Evaluates in O(n) in place of O(n^2) sums involving long-range interaction kernels.

Oldies but goldies: L. Greengard and V. Rokhlin, A Fast Algorithm for Particle Simulations, 1987. Evaluates in O(n) in place of O(n^2) sums involving long-range interaction kernels.

68,683 просмотров

Power iterations converge to the leading eigenvector of a matrix.

Power iterations converge to the leading eigenvector of a matrix.

114,114 просмотров

Large-scale N-body simulations require the evaluation of sums involving long-range interaction kernels. Fast multipoles and Barnes–Hut methods approximate these sums in n*log(n) operations instead of n^2.

Large-scale N-body simulations require the evaluation of sums involving long-range interaction kernels. Fast multipoles and Barnes–Hut methods approximate these sums in n*log(n) operations instead of n^2.

74,712 просмотров

The Cucker-Smale system of ODEs is the simplest model of particles exhibiting flocking behaviors. Diffusion of speeds is governed by a Laplacian on the fully connected graph of points.

The Cucker-Smale system of ODEs is the simplest model of particles exhibiting flocking behaviors. Diffusion of speeds is governed by a Laplacian on the fully connected graph of points.

77,155 просмотров

The three ways to solve Fokker-Planck equations: PDE evolution, stochastic (independent) or deterministic (coupled) particle systems.

The three ways to solve Fokker-Planck equations: PDE evolution, stochastic (independent) or deterministic (coupled) particle systems.

85,333 просмотров

Laplacian eigenmaps perform non-linear dimensionality reduction ("manifold learning") by embedding data points using the eigenvectors of a graph Laplacian as coordinates.

Laplacian eigenmaps perform non-linear dimensionality reduction ("manifold learning") by embedding data points using the eigenvectors of a graph Laplacian as coordinates.

67,799 просмотров

Interpolating at uniformly sampled point can suffer from Runge oscillations. Using Chebyshev nodes resolves this issue.

Interpolating at uniformly sampled point can suffer from Runge oscillations. Using Chebyshev nodes resolves this issue.

78,837 просмотров

Möbius transforms are the bijective conformal maps from the Riemann sphere (complex numbers with a point at infinity) to itself. They are rational functions, form a group under composition, and have, in general, two fixed points (in black).

Möbius transforms are the bijective conformal maps from the Riemann sphere (complex numbers with a point at infinity) to itself. They are rational functions, form a group under composition, and have, in general, two fixed points (in black).

78,030 просмотров

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