VBFF Preprints
R. Baptista, A. M. Stuart, S. Tran; A Mathematical Perspective On Contrastive Learning.
[Preprint]
R. Baptista, P. Birmpa, M. A. Katsoulakis, L. Rey-Bellet, B.J. Zhang; Proximal optimal transport divergences, 2025
[Preprint]
E Bach, R Baptista, E Calvello, B Chen, A Stuart; Learning Enhanced Ensemble Filters, 2025
[Preprint]
L. Conger, F. Hoffmann, R. Baptista, E. Mazumdar; Computing Optimal Transport Plans via Min-Max Gradient Flows, 2025
[Preprint]
R. Baptista, E. Calvello, M. Darcy, H. Owhadi, A. M. Stuart, X. Yang; Solving Roughly Forced Nonlinear PDEs via Misspecified Kernel Methods and Neural Networks, 2025
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R. Baptista, A. Dasgupta, N. B. Kovachki, A. Oberai, A. M. Stuart; Memorization and Regularization in Generative Diffusion Models, 2025
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F. Li, R. Baptista, Y. Marzouk; Expected information gain estimation via density approximations: Sample allocation and dimension reduction, 2024
[Preprint]
E. Bach, R. Baptista, D. Sanz-Alonso, A. Stuart; Inverse Problems and Data Assimilation: A Machine Learning Approach, 2024
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M. Alain, S. Takao, X. Dong, B. Rieck, E. Noutahi; Graph and Simplicial Complex Prediction Gaussian Process via the Hodgelet Representations, 2025.
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P. Grohs, S. Lanthaler, M. Trautner; Theory-to-Practice Gap for Neural Networks and Neural Operators, 2025
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K. Bhattacharya, L. Cao, G. Stepaniants, A. Stuart, M. Trautner; Learning Memory and Material Dependent Constitutive Laws, 2025
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J. Bunker, M. Girolami, H. Lambley, A. M. Stuart, T. J. Sullivan; Autoencoders in Function Space
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M. Sirlanci, G. Hripcsak, C. C. L. Wang, J. N. Stroh, Y. Wang, T. D. Bennett, A. M. Stuart, D. J. Albers; A Stochastic Model-Based Control Methodology for Glycemic Management in the Intensive Care Unit
[Preprint]
E. Calvello, N. B. Kovachki, M. E. Levine, A. M. Stuart; Continuum Attention for Neural Operators
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S. Lanthaler, A. M. Stuart, M. Trautner; Discretization Error of Fourier Neural Operators
[Preprint]
J. A. Carrillo, F. Hoffmann, A. M. Stuart, U. Vaes; Statistical Accuracy of Approximate Filtering Methods
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S. Lanthaler, A. M. Stuart; The Parametric Complexity of Operator Learning
[Perprint]
S. Lanthaler, Z. Li, A. M. Stuart; The Nonlocal Neural Operator: Universal Approximation
[Preprint]
Y. Chen, D. Zhengyu Huang, J. Huang, S. Reich, A. M. Stuart; Gradient Flows for Sampling: Mean-Field Models, Gaussian Approximations and Affine Invariance
[Preprint]
J. A. Carrillo, F. Hoffmann, A. M. Stuart, U. Vaes; The Ensemble Kalman Filter in the Near-Gaussian Setting
[Preprint]
E. Luk, E. Bach, R. Baptista, A.Stuart; Learning Optimal Filters Using Variational Inference
[Preprint]
R. Baptista, E. O'Reilly, Y. Xie;
TrIM: Transformed Iterative Mondrian Forests for Gradient-based Dimension Reduction and High-Dimensional Regression
[Preprint]
M. Provost, R. Baptista, J. Eldredge, Y. Marzouk;
An adaptive ensemble filter for heavy-tailed distributions: tuning-free inflation and localization
[Preprint]
L. Cao, T. O'Leary-Roseberry, O. Ghattas;
Derivative-informed neural operator acceleration of geometric MCMC for infinite-dimensional Bayesian inverse problems
[Preprint]
O. Key, S. Takao, D. Giles, M. Deisenroth;
Scalable Data Assimilation with Message Passing
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E. Carlson, A. Farhat, V. Martinez, C. Victor;
Determining Modes, Synchronization, and Intertwinement
[Preprint]
E. Carlson, A. Farhat, V. Martinez, C. Victor;
On the Infinite-Nudging Limit of the Nudging Filter for Continuous Data Assimilation
[Preprint]
