9 citations · 25 across the 10 of their papers we have counts for
4 papers · 1 filter
Averaged Mirror Descent and Dual Gradient Methods: Convergent Algorithms for Entropic Gromov-Wasserstein Problems
Joanna Marks, Joanna Mark, Gabriel Rioux +2
The Gromov-Wasserstein (GW) distance measures the discrepancy between metric measure (mm) spaces and identifies optimal alignments between them based solely on their intrinsic stru…
Discrete Gromov-Wasserstein Duality: Algorithms and Isomorphism Testing
Gabriel Rioux, Joanna Marks, Riccardo Passeggeri +1
The Gromov-Wasserstein (GW) distance provides a principled framework for aligning metric measure (mm) spaces based solely on their intrinsic structure. Its ability to identify isom…
On the Computational and Statistical Efficiency of the Empirical Maximum Entropy on the Mean Method
Matthew King-Roskamp, Gabriel Rioux, Rustum Choksi +1
The Maximum Entropy on the Mean (MEM) method provides a flexible computational framework for solving inverse problems by combining data fidelity with entropy-based regularization.…
Sliced Inner Product Gromov-Wasserstein Distances
Xiaoyun Gong, Gabriel Rioux, Ziv Goldfeld
The Gromov-Wasserstein (GW) problem provides a framework for aligning heterogeneous datasets by matching their intrinsic geometry, but its statistical and computational scaling rem…