CV

Education

• Ph.D in Version Control Theory, GitHub University, 2018 (expected)
• M.S. in Jekyll, GitHub University, 2014
• B.S. in GitHub, GitHub University, 2012

Work experience

• Spring 2024: Academic Pages Collaborator
  • GitHub University
  • Duties includes: Updates and improvements to template
  • Supervisor: The Users
• Fall 2015: Research Assistant
  • GitHub University
  • Duties included: Merging pull requests
  • Supervisor: Professor Hub
• Summer 2015: Research Assistant
  • GitHub University
  • Duties included: Tagging issues
  • Supervisor: Professor Git

Skills

• Skill 1
• Skill 2
  • Sub-skill 2.1
  • Sub-skill 2.2
  • Sub-skill 2.3
• Skill 3

Publications

Averaged Mirror Descent and Dual Gradient Methods: Convergent Algorithms for Entropic Gromov-Wasserstein Problem

J. Marks^★, G. Rioux^★, and R. Passeggeri. "Averaged Mirror Descent and Dual Gradient Methods: Convergent Algorithms for Entropic Gromov-Wasserstein Problem" arXiv preprint. arXiv:2609.31848, 2026.

Discrete Gromov-Wasserstein Duality: Algorithms and Isomorphism Testing

G. Rioux^★, J. Marks, R. Passeggeri, and Z. Goldfeld. "Discrete Gromov-Wasserstein Duality: Algorithms and Isomorphism Testing" arXiv preprint. arXiv:2609.03094, 2026.

On the Computational and Statistical Efficiency of the Empirical Maximum Entropy on the Mean Method

M. King-Roskamp^★, G. Rioux^★, R. Choksi, and T. Hoheisel. "On the Computational and Statistical Efficiency of the Empirical Maximum Entropy on the Mean Method s" arXiv preprint. arXiv:2608.27705, 2026.

Sliced Inner Product Gromov-Wasserstein Distances

X. Gong^★, G. Rioux^★, and Z. Goldfeld. "Sliced Inner Product Gromov-Wasserstein Distances" Accepted at Advances in Neural Information Processing Systems. 40, 2026.

Approximation Analysis of the Entropic Penalty in Quadratic Programming

V. Karumanchi^★, G. Rioux^★, and Z. Goldfeld. "Approximation Analysis of the Entropic Penalty in Quadratic Programming." arXiv preprint. arXiv:2509.20031, 2025.

Limit Laws for Gromov-Wasserstein Alignment with Applications to Testing Graph Isomorphisms

G. Rioux^★, Z. Goldfeld, and K. Kato. "Limit Laws for Gromov-Wasserstein Alignment with Applications to Testing Graph Isomorphisms." arXiv preprint. arXiv:2410.18006, 2024.

Entropic Gromov-Wasserstein distances: Stability and algorithms

G. Rioux^★, Z. Goldfeld, and K. Kato. "Entropic Gromov-Wasserstein Distances: Stability and algorithms." Journal of Machine Learning Research. 25(363), 2024, pp.1-52.

Multivariate stochastic dominance via optimal transport and applications to models benchmarking

G. Rioux^★, A. Nitsure, M. Rigotti, K, Greenewald, and Y. Mroueh. "Multivariate stochastic dominance via optimal transport and applications to models benchmarking." Advances in Neural Information Processing Systems. 37, 2024, pp.39190-39223.

Limit theorems for entropic optimal transport maps and the Sinkhorn divergence

Z. Goldfeld, K. Kato, S. Nietert, and G. Rioux. "Limit theorems for entropic optimal transport maps and the Sinkhorn divergence." Electronic Journal of Statistics. 34(2), 18(1), 2024, pp.980-1041.

Statistical inference with regularized optimal transport

Z. Goldfeld, K. Kato, G. Rioux, and R. Sadhu. "Statistical inference with regularized optimal transport." Information and Inference: A Journal of the IMA. 13(1), 2024.

Limit distribution theory for smooth p-Wasserstein distances

Z. Goldfeld, K. Kato, S. Nietert, and G. Rioux. "Limit distribution theory for smooth p-Wasserstein distances." Annals of Applied Probability. 34(2), 2024, pp.2447-2487.

The Maximum Entropy on the Mean Method for Image Deblurring

G. Rioux^★, R. Choksi, T. Hoheisel, C. Scarvelis, and P. Maréchal. "The Maximum Entropy on the Mean Method for Image Deblurring." Inverse Problems. 37, 2021 (29 pp.).

Blind Deblurring of Barcodes via Kullback-Leibler Divergence

G. Rioux^★, C. Scarvelis^★, R. Choksi, T. Hoheisel, and P. Maréchal. "Blind Deblurring of Barcodes via Kullback-Leibler Divergence." IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(1), 2021, pp.77-88.

Talks

Conference Proceeding talk 3 on Relevant Topic in Your Field

March 01, 2014

Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA, USA

Talk 2 on Relevant Topic in Your Field

February 01, 2014

Talk at London School of Testing, London, UK

Tutorial 1 on Relevant Topic in Your Field

March 01, 2013

Tutorial at UC-Berkeley Institute for Testing Science, Berkeley, CA, USA

Talk 1 on Relevant Topic in Your Field

March 01, 2012

Talk at UC San Francisco, Department of Testing, San Francisco, CA, USA

Teaching

Statistical Theory

Fundamentals of Machine Learning

Optimal transport theory and statistical divergences

Fundamentals of Machine Learning

Information Theory

Introduction to Differential Equationss

Introduction to Partial Differential Equations

Differential Equations for Engineers

Service and leadership

• Currently signed in to 43 different slack teams