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ViktorAJStein/README.md

Hi there 👋

I am a second-year PhD candidate in Applied Mathematics at TU Berlin under the supervision of Prof. Gabriele Steidl.

My interests lie in optimal transport, primarily in Wasserstein gradient flows, and in kernel methods. I am currenly learning more about metric gradient flows for other geometries, e.g., like SVGD.

Here you will find the code for the following projects.

Contact

stein[at]math[dot]tu-berlin[dot]de

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  1. MMD_Wasserstein_gradient_flow_on_the_line MMD_Wasserstein_gradient_flow_on_the_line Public

    Implicit and explicit Euler schemes for Wasserstein gradient flow of the Maximum Mean Discrepancy (MMD) with respect to the negative distance kernel on the line.

    Python 2

  2. Regularized_f_Divergence_Particle_Flows Regularized_f_Divergence_Particle_Flows Public

    Discretized Wasserstein Particle Flows of a MMD-regularized f-divergence functional.

    Python 1 1