Preprints and publications are presented in reverse chronological order.


  1. arXiv
    Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
    Zheyu Oliver Wang, Ricardo Baptista, Youssef Marzouk, Lars Ruthotto, and Deepanshu Verma
    arXiv:2310.16975, 2023
  2. FoCM
    On the representation and learning of monotone triangular transport maps
    Ricardo Baptista, Youssef Marzouk, and Olivier Zahm
    Foundations of Computational Mathematics, 2023
  3. NeurIPS
    Debias Coarsely, Sample Conditionally: Statistical Downscaling through Optimal Transport and Probabilistic Diffusion Models
    Zhong Yi Wan, Ricardo Baptista, Yi-fan Chen, John Anderson, Anudhyan Boral, Fei Sha, and Leonardo Zepeda-Núñez
    In Advances in Neural Information Processing Systems, 2023
  4. NeurIPS OTML
    A generative flow model for conditional sampling via optimal transport
    Jason Alfonso, Ricardo Baptista, Anupam Bhakta, Noam Gal, Alfin Hou, Isa Lyubimova, Daniel Pocklington, Josef Sajonz, Giulio Trigila, and Ryan Tsai
    In NeurIPS Optimal Transport and Machine Learning Workshop, 2023
  5. arXiv
    An approximation theory framework for measure-transport sampling algorithms
    Ricardo Baptista, Bamdad Hosseini, Nikola B Kovachki, Youssef M Marzouk, and Amir Sagiv
    arXiv:2302.13965, 2023
  6. JCP
    Ensemble transport smoothing.–Part 1: Unified framework
    Maximilian Ramgraber, Ricardo Baptista, Dennis McLaughlin, and Youssef Marzouk
    Journal of Computational Physics: X, 2023
  7. JCP
    Ensemble transport smoothing.–Part 2: Nonlinear updates
    Maximilian Ramgraber, Ricardo Baptista, Dennis McLaughlin, and Youssef Marzouk
    Journal of Computational Physics: X, 2023
  8. arXiv
    An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localization
    Mathieu Le Provost, Ricardo Baptista, Youssef Marzouk, and Jeff D Eldredge
    arXiv:2310.08741, 2023
    Computational Optimal Transport and Filtering on Riemannian manifolds
    Daniel Grange, Mohammad Al-Jarrah, Ricardo Baptista, Amirhossein Taghvaei, Tryphon T Georgiou, and Allen Tannenbaum
    IEEE Control Systems Letters, 2023
  10. NeurIPS
    Structured Neural Networks for Density Estimation and Causal Inference
    Asic Q Chen, Ruian Shi, Xiang Gao, Ricardo Baptista, and Rahul G Krishnan
    In Advances in Neural Information Processing Systems, 2023
  11. arXiv
    Score-based diffusion models in function space
    Jae Hyun Lim, Nikola B Kovachki, Ricardo Baptista, Christopher Beckham, Kamyar Azizzadenesheli, Jean Kossaifi, Vikram Voleti, Jiaming Song, Karsten Kreis, Jan Kautz, and 1 more author
    arXiv:2302.07400, 2023
  12. arXiv
    Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference
    Ricardo Baptista, Bamdad Hosseini, Nikola B Kovachki, and Youssef Marzouk
    arXiv:2006.06755, 2023


  1. SIAM Review
    Coupling techniques for nonlinear ensemble filtering
    Alessio Spantini, Ricardo Baptista, and Youssef Marzouk
    SIAM Review, 2022
  2. NeurIPS SBM
    Dimension reduction via score ratio matching
    Michael Brennan, Ricardo Baptista, and Youssef Marzouk
    In NeurIPS 2022 Workshop on Score-Based Methods, 2022
  3. JOSS
    MParT: Monotone Parameterization Toolkit
    Matthew Parno, Paul-Baptiste Rubio, Daniel Sharp, Michael Brennan, Ricardo Baptista, Henning Bonart, and Youssef Marzouk
    Journal of Open Source Software, 2022
  4. JMA
    Diagonal nonlinear transformations preserve structure in covariance and precision matrices
    Rebecca Morrison, Ricardo Baptista, and Estelle Basor
    Journal of Multivariate Analysis, 2022
  5. arXiv
    Gradient-based data and parameter dimension reduction for Bayesian models: an information theoretic perspective
    Ricardo Baptista, Youssef Marzouk, and Olivier Zahm
    arXiv:2207.08670, 2022
  6. arXiv
    Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport
    Ricardo Baptista, Lianghao Cao, Joshua Chen, Omar Ghattas, Fengyi Li, Youssef M Marzouk, and J Tinsley Oden
    arXiv:2206.11343, 2022
  7. PRSA
    A low-rank ensemble Kalman filter for elliptic observations
    Mathieu Le Provost, Ricardo Baptista, Youssef Marzouk, and Jeff D Eldredge
    Proceedings of the Royal Society A, 2022


  1. arXiv
    Learning non-Gaussian graphical models via Hessian scores and triangular transport
    Ricardo Baptista, Youssef Marzouk, Rebecca E Morrison, and Olivier Zahm
    arXiv:2101.03093, 2021
  2. AIAA
    A low-rank nonlinear ensemble filter for vortex models of aerodynamic flows
    Mathieu Le Provost, Ricardo Baptista, Youssef Marzouk, and Jeff Eldredge
    In AIAA Scitech 2021 Forum, 2021


  1. SEG
    Bayesian seismic inversion: Measuring Langevin MCMC sample quality with kernels
    Muhammad Izzatullah, Ricardo Baptista, Lester Mackey, Youssef Marzouk, and Daniel Peter
    In SEG International Exposition and Annual Meeting, 2020


  1. JCP
    Some greedy algorithms for sparse polynomial chaos expansions
    Ricardo Baptista, Valentin Stolbunov, and Prasanth B Nair
    Journal of Computational Physics, 2019


  1. ICML
    Bayesian optimization of combinatorial structures
    Ricardo Baptista, and Matthias Poloczek
    In International Conference on Machine Learning, 2018
  2. AIAA
    Optimal approximations of coupling in multidisciplinary models
    Ricardo Baptista, Youssef Marzouk, Karen Willcox, and Benjamin Peherstorfer
    AIAA Journal, 2018


  1. NeurIPS
    Beyond normality: learning sparse probabilistic graphical models in the non-Gaussian setting
    Rebecca E Morrison, Ricardo Baptista, and Youssef Marzouk
    In Proceedings of the 31st International Conference on Neural Information Processing Systems, 2017