Skip to content

kernax.quantization

Module for kernel quantization using maximum mean discrepancy.

KernelHerding

Bases: Module

Greedy MMD-based kernel quantization (herding-style thinning).

Once instantiated, the module can be called with an integer m to select m representative samples from the input dataset.

Parameters:

  • x –

    The dataset of shape (N, d) to be subsampled.

  • kernel_fn –

    Kernel function of the form k(x: (d,), y: (d,)) -> scalar.

__call__ 

__call__(m)

Return indices of a subset (size m) that greedily minimizes MMD.

Parameters:

  • m (int) –

    Number of points to select (must be <= N).

Returns:

  • JaxArray –

    Indices of the selected points into x, array of shape (m,).