Fast and smooth interpolation on wasserstein space S Chewi, J Clancy, T Le Gouic, P Rigollet, G Stepaniants, A Stromme International Conference on Artificial Intelligence and Statistics, 3061-3069, 2021 | 31 | 2021 |
Inferring causal networks of dynamical systems through transient dynamics and perturbation G Stepaniants, BW Brunton, JN Kutz Physical Review E 102 (4), 042309, 2020 | 22 | 2020 |
Learning partial differential equations in reproducing kernel Hilbert spaces G Stepaniants Journal of Machine Learning Research 24 (86), 1-72, 2023 | 18 | 2023 |
GULP: a prediction-based metric between representations E Boix-Adsera, H Lawrence, G Stepaniants, P Rigollet Advances in Neural Information Processing Systems 35, 7115-7127, 2022 | 8 | 2022 |
Discovering dynamics and parameters of nonlinear oscillatory and chaotic systems from partial observations G Stepaniants, AD Hastewell, DJ Skinner, JF Totz, J Dunkel Physical Review Research 6 (4), 043062, 2024 | 5 | 2024 |
Covariance alignment: from maximum likelihood estimation to Gromov-Wasserstein Y Han, P Rigollet, G Stepaniants arXiv preprint arXiv:2311.13595, 2023 | 3 | 2023 |
The Lebesgue Integral, Chebyshev’s Inequality, and the Weierstrass Approximation Theorem G Stepaniants Webpage, 2017 | 2 | 2017 |
Optimal transport for automatic alignment of untargeted metabolomic data M Breeur, G Stepaniants, P Keski-Rahkonen, P Rigollet, V Viallon eLife 12, RP91597, 2024 | 1 | 2024 |
Inference from Limited Observations in Statistical, Dynamical, and Functional Problems G Stepaniants Massachusetts Institute of Technology, 2024 | | 2024 |