Baptista, Ricardo

16 publications

AISTATS 2025 Conditional Simulation via Entropic Optimal Transport: Toward Non-Parametric Estimation of Conditional Brenier Maps Ricardo Baptista, Aram-Alexandre Pooladian, Michael Brennan, Youssef Marzouk, Jonathan Niles-Weed
TMLR 2025 Dimension Reduction via Score Ratio Matching Ricardo Baptista, Michael Brennan, Youssef Marzouk
TMLR 2025 Ensemble Kalman Diffusion Guidance: A Derivative-Free Method for Inverse Problems Hongkai Zheng, Wenda Chu, Austin Wang, Nikola Borislavov Kovachki, Ricardo Baptista, Yisong Yue
ICLRW 2025 Ensemble Kalman Sampling and Diffusion Prior in Tandem: A Split Gibbs Framework Austin Wang, Hongkai Zheng, Zihui Wu, Ricardo Baptista, Daniel Zhengyu Huang, Yisong Yue
AAAI 2025 Learning Local Neighborhoods of Non-Gaussian Graphical Models Sarah Liaw, Rebecca E. Morrison, Youssef M. Marzouk, Ricardo Baptista
ICLR 2025 Neural Approximate Mirror Maps for Constrained Diffusion Models Berthy Feng, Ricardo Baptista, Katherine Bouman
JMLR 2025 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, Christopher Pal, Arash Vahdat, Anima Anandkumar
NeurIPSW 2024 Consensus Based Optimization Accelerates Gradient Descent Anagha Satish, Ricardo Baptista, Franca Hoffmann
JMLR 2024 Learning Non-Gaussian Graphical Models via Hessian Scores and Triangular Transport Ricardo Baptista, Rebecca Morrison, Olivier Zahm, Youssef Marzouk
NeurIPSW 2023 A Generative Flow Model for Conditional Sampling via Optimal Transport Jason Alfonso, Ricardo Baptista, Anupam Bhakta, Noam Gal, Alfin Hou, Vasilisa Lyubimova, Daniel Pocklington, Josef Sajonz, Giulio Trigila, Ryan Tsai
NeurIPS 2023 Debias Coarsely, Sample Conditionally: Statistical Downscaling Through Optimal Transport and Probabilistic Diffusion Models Zhong Yi Wan, Ricardo Baptista, Anudhyan Boral, Yi-Fan Chen, John Anderson, Fei Sha, Leonardo Zepeda-Núñez
ICMLW 2023 Structured Neural Networks for Density Estimation Asic Q Chen, Ruian Shi, Xiang Gao, Ricardo Baptista, Rahul G Krishnan
NeurIPS 2023 Structured Neural Networks for Density Estimation and Causal Inference Asic Chen, Ruian Shi, Xiang Gao, Ricardo Baptista, Rahul G Krishnan
NeurIPSW 2022 Dimension Reduction via Score Ratio Matching Michael Brennan, Ricardo Baptista, Youssef Marzouk
ICML 2018 Bayesian Optimization of Combinatorial Structures Ricardo Baptista, Matthias Poloczek
NeurIPS 2017 Beyond Normality: Learning Sparse Probabilistic Graphical Models in the Non-Gaussian Setting Rebecca Morrison, Ricardo Baptista, Youssef Marzouk