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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. Paper | Bibtex

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.). Paper | ArXiv | Bibtex

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. Paper | ArXiv | Bibtex

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. Paper | ArXiv | Bibtex

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. Paper | ArXiv | Bibtex

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. Paper | ArXiv | Bibtex

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. Paper | ArXiv | Bibtex

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. ArXiv | Bibtex

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

Teaching Assistant, Differential Equations for Engineers, Cornell University, Fall 2020

Teaching Assistant, Introduction to Partial Differential Equations, Cornell University, Spring 2021

Teaching Assistant, Introduction to Differential Equationss, Cornell University, Fall 2021

Grader, Information Theory, Cornell University, Fall 2023

Grader, Fundamentals of Machine Learning, Cornell University, Spring 2024

Grader, Optimal transport theory and statistical divergences, Cornell University, Fall 2024

Grader, Fundamentals of Machine Learning, Cornell University, Spring 2025

Instructor, Statistical Theory, Imperial College London, Fall 2025