Daniele E. Schiavazzi

30 papers Journal 30

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Conditional Normalizing Flows for Forward and Backward Joint State and Parameter Estimation. CoRR Luke S. Lagunowich, Guoxiang Grayson Tong, Daniele E. Schiavazzi
2026	J	`jnl`	FalconBC: Flow matching for Amortized inference of Latent-CONditioned physiologic Boundary Conditions. CoRR Chloe H. Choi, Alison L. Marsden, Daniele E. Schiavazzi
2026	J	`jnl`	On the accuracy of implicit neural representations for cardiovascular anatomies and hemodynamic fields. Comput. Biol. Medicine Jubilee Lee, Daniele E. Schiavazzi
2026	J	`jnl`	On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiological boundary conditions. Comput. Biol. Medicine Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi, Alison L. Marsden
2025	J	`jnl`	Assessing the performance of correlation-based multi-fidelity neural emulators. CoRR Cristian J. Villatoro, Gianluca Geraci, Daniele E. Schiavazzi
2025	J	`jnl`	Enabling stratified sampling in high dimensions via nonlinear dimensionality reduction. CoRR Gianluca Geraci, Daniele E. Schiavazzi, Andrea Zanoni
2025	J	`jnl`	Neural Active Manifolds: Nonlinear Dimensionality Reduction for Uncertainty Quantification. J. Sci. Comput. Andrea Zanoni, Gianluca Geraci, Matteo Salvador, Alison L. Marsden, Daniele E. Schiavazzi
2025	J	`jnl`	On the accuracy of implicit neural representations for cardiovascular anatomies and hemodynamic fields. CoRR Jubilee Lee, Daniele E. Schiavazzi
2025	J	`jnl`	On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiologic boundary conditions. CoRR Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi, Alison L. Marsden
2025	J	`jnl`	Optimal patient allocation for echocardiographic assessments. CoRR Bozhi Sun, Seda Tierney, Jeffrey A. Feinstein, Frederick Damen, Alison L. Marsden, Daniele E. Schiavazzi
2025	J	`jnl`	Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification. Comput. Methods Programs Biomed. Karthik Menon, Andrea Zanoni, Muhammad Owais Khan, Gianluca Geraci, Koen Nieman, Daniele E. Schiavazzi, Alison L. Marsden
2024	J	`jnl`	Bayesian Windkessel calibration using optimized 0D surrogate models. CoRR Jakob Richter, Jonas Nitzler, Luca Pegolotti, Karthik Menon, Jonas Biehler, Wolfgang A. Wall, Daniele E. Schiavazzi, Alison L. Marsden, Martin R. Pfaller
2024	J	`jnl`	InVAErt networks for amortized inference and identifiability analysis of lumped parameter hemodynamic models. CoRR Guoxiang Grayson Tong, Carlos A. Sing-Long, Daniele E. Schiavazzi
2024	J	`jnl`	LINFA: a Python library for variational inference with normalizing flow and annealing. J. Open Source Softw. Yu Wang, Emma R. Cobian, Jubilee Lee, Fang Liu, Jonathan D. Hauenstein, Daniele E. Schiavazzi
2024	J	`jnl`	NeurAM: nonlinear dimensionality reduction for uncertainty quantification through neural active manifolds. CoRR Andrea Zanoni, Gianluca Geraci, Matteo Salvador, Alison L. Marsden, Daniele E. Schiavazzi
2024	J	`jnl`	Personalized and uncertainty-aware coronary hemodynamics simulations: From Bayesian estimation to improved multi-fidelity uncertainty quantification. CoRR Karthik Menon, Andrea Zanoni, Muhammad Owais Khan, Gianluca Geraci, Koen Nieman, Daniele E. Schiavazzi, Alison L. Marsden
2024	J	`jnl`	Quantification of total uncertainty in the physics-informed reconstruction of CVSim-6 physiology. CoRR Mario De Florio, Zongren Zou, Daniele E. Schiavazzi, George Em Karniadakis
2023	J	`jnl`	A Probabilistic Neural Twin for Treatment Planning in Peripheral Pulmonary Artery Stenosis. CoRR 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
2023	J	`jnl`	An analysis of reconstruction noise from undersampled 4D flow MRI. Biomed. Signal Process. Control. Lauren Partin, Daniele E. Schiavazzi, Carlos A. Sing-Long
2023	J	`jnl`	Differentially Private Normalizing Flows for Density Estimation, Data Synthesis, and Variational Inference with Application to Electronic Health Records. CoRR Bingyue Su, Yu Wang, Daniele E. Schiavazzi, Fang Liu
2023	J	`jnl`	InVAErt networks: a data-driven framework for emulation, inference and identifiability analysis. CoRR Guoxiang Grayson Tong, Carlos A. Sing-Long, Daniele E. Schiavazzi
2023	J	`jnl`	LINFA: a Python library for variational inference with normalizing flow and annealing. CoRR Yu Wang, Emma R. Cobian, Jubilee Lee, Fang Liu, Jonathan D. Hauenstein, Daniele E. Schiavazzi
2023	J	`jnl`	Multifidelity data fusion in convolutional encoder/decoder networks. J. Comput. Phys. Lauren Partin, Gianluca Geraci, Ahmad A. Rushdi, Michael S. Eldred, Daniele E. Schiavazzi
2022	J	`jnl`	AdaAnn: Adaptive Annealing Scheduler for Probability Density Approximation. CoRR Emma R. Cobian, Jonathan D. Hauenstein, Fang Liu, Daniele E. Schiavazzi
2022	J	`jnl`	An analysis of reconstruction noise from undersampled 4D flow MRI. CoRR Lauren Partin, Daniele E. Schiavazzi, Carlos A. Sing-Long
2022	J	`jnl`	Data-driven synchronization-avoiding algorithms in the explicit distributed structural analysis of soft tissue. CoRR Guoxiang Grayson Tong, Daniele E. Schiavazzi
2022	J	`jnl`	Multifidelity data fusion in convolutional encoder/decoder networks. CoRR Lauren Partin, Gianluca Geraci, Ahmad A. Rushdi, Michael S. Eldred, Daniele E. Schiavazzi
2022	J	`jnl`	Variational inference with NoFAS: Normalizing flow with adaptive surrogate for computationally expensive models. J. Comput. Phys. Yu Wang, Fang Liu, Daniele E. Schiavazzi
2021	J	`jnl`	An ensemble solver for segregated cardiovascular FSI. CoRR Xue Li, Daniele E. Schiavazzi
2021	J	`jnl`	Variational Inference with NoFAS: Normalizing Flow with Adaptive Surrogate for Computationally Expensive Models. CoRR Yu Wang, Fang Liu, Daniele E. Schiavazzi