import * as tf from '../tf-adapter';
/**
 * Returns the `k` smallest eigenvectors AND eigenvalues of the provided symmetric matrix.
 * This is needed to apply diffusion map scaling like sklearn does.
 */
export declare function smallest_eigenvectors_with_values(matrix: tf.Tensor2D, k: number): {
    eigenvectors: tf.Tensor2D;
    eigenvalues: tf.Tensor1D;
};
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