Youssef Marzouk

IIT@MIT — United States

Computer Science · Physical Sciences

36h-index5.7kcitations332works1.92yr avg
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Research Topics

Gaussian Processes and Bayesian Inference(71), Markov Chains and Monte Carlo Methods(69), Probabilistic and Robust Engineering Design(65), Statistical Methods and Inference(44), Model Reduction and Neural Networks(28)

Publications332 total

Learning Paths for Dynamic Measure Transport: A Control Perspective
arXiv (Cornell University)·2025Open Access
Neural Triangular Transport Maps: A New Approach Towards Sampling in Lattice QCD
arXiv (Cornell University)·2025Open Access
An Eulerian Perspective on Straight-Line Sampling
arXiv (Cornell University)·2025Open Access
Uncertainty Quantification of Fluid Leakage and Fault Instability in Geologic CO2 ${\text{CO}}_{2}$ Storage
Water Resources Research·2025Open Access
Data Assimilation: From Mathematical and Statistical Foundations to Applications
Oberwolfach Reports·2025Open Access
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference
SIAM Journal on Scientific Computing·2025· 1 cited
Editorial: Generative Artificial Intelligence for Predictive Simulations and Decision-Making in Science and Engineering
Computer Methods in Applied Mechanics and Engineering·2025
Canonical Bayesian Linear System Identification
arXiv (Cornell University)·2025Open Access
Discussion of “Experimental Design and Modeling for Forward-Inverse Maps” by R. Barton &amp; M. Morris, appearing in <i>Technometrics</i>
Technometrics·2025
Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities
Information and Inference A Journal of the IMA·2025Open Access
Stable generative modelling using Schrödinger bridges
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences·2025· 1 cited
Distributionally robust Gaussian process regression and Bayesian inverse problems
The Annals of Applied Probability·2025
Efficient sampling for sparse Bayesian learning using hierarchical prior normalization
arXiv (Cornell University)·2025Open Access
Localized Diffusion Models
arXiv (Cornell University)·2025Open Access
Priorconditioned Sparsity-Promoting Projection Methods for Deterministic and Bayesian Linear Inverse Problems
arXiv (Cornell University)·2025Open Access
Bayesian optimal experimental design with Wasserstein information criteria
arXiv (Cornell University)·2025Open Access
Learning Local Neighborhoods of Non-Gaussian Graphical Models
Proceedings of the AAAI Conference on Artificial Intelligence·2025Open Access
A friendly introduction to triangular transport
arXiv (Cornell University)·2025Open Access
Conformal Prediction under Levy-Prokhorov Distribution Shifts: Robustness to Local and Global Perturbations
arXiv (Cornell University)·2025Open Access
Weighted quantization using MMD: From mean field to mean shift via gradient flows
arXiv (Cornell University)·2025Open Access
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Frequent Co-authors

Tiangang Cui(9), Alessio Spantini(8), Karen Willcox(5), Olivier Zahm(5), Habib N. Najm(4), Xun Huan(4), Tarek Moselhy(4), Ahmed F. Ghoniem(4), Kody J. H. Law(3), Patrick R. Conrad(3), Matthew Parno(3), Mark Chilenski(2), M. Greenwald(2), A. E. White(2), J. E. Rice(2), Weiqi Ji(2), Zhuyin Ren(2), Chung K. Law(2), Omar Knio(2), Antti Solonen(2)