A matching pursuit approach to solenoidal filtering of three-dimensional velocity measurements. - Daniele Schiavazzi; Filippo Coletti; Gianluca Iaccarino; John K. Eaton (J. Comput. Phys., 2014)

Geometric Uncertainty in Patient-Specific Cardiovascular Modeling with Convolutional Dropout Networks. - Gabriel D. Maher; Casey Fleeter; Daniele Schiavazzi; Alison L. Marsden (CoRR, 2020)

An ensemble solver for segregated cardiovascular FSI. - Xue Li; Daniele E. Schiavazzi (CoRR, 2021)

AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation. - Emma R. Cobian; Jonathan D. Hauenstein; Fang Liu 006; Daniele E. Schiavazzi (CoRR, 2022)

Data-driven synchronization-avoiding algorithms in the explicit distributed structural analysis of soft tissue. - Guoxiang Grayson Tong; Daniele E. Schiavazzi (CoRR, 2022)

Variational inference with NoFAS: Normalizing flow with adaptive surrogate for computationally expensive models. - Yu Wang; Fang Liu 006; Daniele E. Schiavazzi (J. Comput. Phys., 2022)

Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records. - Bingyue Su; Yu Wang; Daniele E. Schiavazzi; Fang Liu 006 (CoRR, 2023)

InVAErt networks: a data-driven framework for emulation, inference and identifiability analysis. - Guoxiang Grayson Tong; Carlos A. Sing-Long; Daniele E. Schiavazzi (CoRR, 2023)

A Probabilistic Neural Twin for Treatment Planning in Peripheral Pulmonary Artery Stenosis. - John D. Lee; Jakob Richter; Martin R. Pfaller; Jason M. Szafron; Karthik Menon; Andrea Zanoni; Michael R. Ma; Jeffrey A. Feinstein; Jacqueline Kreutzer; Alison L. Marsden; Daniele E. Schiavazzi (CoRR, 2023)

Multifidelity data fusion in convolutional encoder/decoder networks. - Lauren Partin; Gianluca Geraci; Ahmad A. Rushdi; Michael S. Eldred; Daniele E. Schiavazzi (J. Comput. Phys., 2023)

An analysis of reconstruction noise from undersampled 4D flow MRI. - Lauren Partin; Daniele E. Schiavazzi; Carlos A. Sing-Long (Biomed. Signal Process. Control., 2023)

Bayesian Windkessel calibration using optimized 0D surrogate models. - Jakob Richter; Jonas Nitzler; Luca Pegolotti; Karthik Menon; Jonas Biehler; Wolfgang A. Wall; Daniele E. Schiavazzi; Alison L. Marsden; Martin R. Pfaller (CoRR, 2024)

NeurAM: nonlinear dimensionality reduction for uncertainty quantification through neural active manifolds. - Andrea Zanoni; Gianluca Geraci; Matteo Salvador; Alison L. Marsden; Daniele E. Schiavazzi (CoRR, 2024)

Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology. - Mario De Florio; Zongren Zou; Daniele E. Schiavazzi; George Em Karniadakis (CoRR, 2024)

InVAErt networks for amortized inference and identifiability analysis of lumped parameter hemodynamic models. - Guoxiang Grayson Tong; Carlos A. Sing-Long; Daniele E. Schiavazzi (CoRR, 2024)

LINFA: a Python library for variational inference with normalizing flow and annealing. - Yu Wang; Emma R. Cobian; Jubilee Lee; Fang Liu 006; Jonathan D. Hauenstein; Daniele E. Schiavazzi (J. Open Source Softw., 2024)

Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification. - Karthik Menon; Andrea Zanoni; Muhammad Owais Khan; Gianluca Geraci; Koen Nieman; Daniele E. Schiavazzi; Alison L. Marsden (Comput. Methods Programs Biomed., 2025)

Optimal patient allocation for echocardiographic assessments. - Bozhi Sun; Seda Tierney; Jeffrey A. Feinstein; Frederick Damen; Alison L. Marsden; Daniele E. Schiavazzi (CoRR, 2025)

Enabling stratified sampling in high dimensions via nonlinear dimensionality reduction. - Gianluca Geraci; Daniele E. Schiavazzi; Andrea Zanoni (CoRR, 2025)

On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiologic boundary conditions. - Chloe H. Choi; Andrea Zanoni; Daniele E. Schiavazzi; Alison L. Marsden (CoRR, 2025)