no code implementations • 13 May 2020 • Gennaro Auricchio, Andrea Codegoni, Stefano Gualandi, Giuseppe Toscani, Marco Veneroni
We investigate properties of some extensions of a class of Fourier-based probability metrics, originally introduced to study convergence to equilibrium for the solution to the spatially homogeneous Boltzmann equation.
no code implementations • NeurIPS 2018 • Gennaro Auricchio, Federico Bassetti, Stefano Gualandi, Marco Veneroni
This paper presents a novel method to compute the exact Kantorovich-Wasserstein distance between a pair of $d$-dimensional histograms having $n$ bins each.
1 code implementation • NeurIPS 2018 • Gennaro Auricchio, Federico Bassetti, Stefano Gualandi, Marco Veneroni
This paper presents a novel method to compute the exact Kantorovich-Wasserstein distance between a pair of $d$-dimensional histograms having $n$ bins each.
3 code implementations • 2 Apr 2018 • Federico Bassetti, Stefano Gualandi, Marco Veneroni
When the distance among bins is measured with the 2-norm: (i) we derive a quantitative estimate on the error between optimal and approximate solution; (ii) given the error, we construct a reduced flow network of size $O(n)$.
