Fast and Smooth Interpolation on Wasserstein Space. - Sinho Chewi; Julien Clancy; Thibaut Le Gouic; Philippe Rigollet; George Stepaniants; Austin J. Stromme (AISTATS, 2021)

GULP: a prediction-based metric between representations. - Enric Boix-Adserà; Hannah Lawrence; George Stepaniants; Philippe Rigollet (NeurIPS, 2022)

Optimal transport for automatic alignment of untargeted metabolomic data. - Marie Breeur; George Stepaniants; Pekka Keski-Rahkonen; Philippe Rigollet; Vivian Viallon (CoRR, 2023)

Covariance alignment: from maximum likelihood estimation to Gromov-Wasserstein. - Yanjun Han; Philippe Rigollet; George Stepaniants (CoRR, 2023)

Learning Partial Differential Equations in Reproducing Kernel Hilbert Spaces. - George Stepaniants (J. Mach. Learn. Res., 2023)

Learning Memory and Material Dependent Constitutive Laws. - Kaushik Bhattacharya; Lianghao Cao; George Stepaniants; Andrew M. Stuart; Margaret Trautner (CoRR, 2025)