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2020 – today
- 2025
[j26]Linus Seelinger
, Anne Reinarz, Mikkel Bue Lykkegaard, Robert Akers, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Benjamin M. Kent, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl:
Democratizing uncertainty quantification. J. Comput. Phys. 521: 113542 (2025)- 2024
- [j25]Thomas O'Leary-Roseberry, Peng Chen, Umberto Villa, Omar Ghattas:
Derivative-Informed Neural Operator: An efficient framework for high-dimensional parametric derivative learning. J. Comput. Phys. 496: 112555 (2024) - [j24]Dingcheng Luo, Peng Chen, Thomas O'Leary-Roseberry, Umberto Villa, Omar Ghattas:
SOUPy: Stochastic PDE-constrained optimization under high-dimensional uncertainty in Python. J. Open Source Softw. 9(99): 6101 (2024) - [j23]Luke Lozenski, Hanchen Wang, Fu Li, Mark A. Anastasio, Brendt Wohlberg, Youzuo Lin, Umberto Villa:
Learned Full Waveform Inversion Incorporating Task Information for Ultrasound Computed Tomography. IEEE Trans. Computational Imaging 10: 69-82 (2024) - [j22]Luke Lozenski, Refik Mert Çam, Mark D. Pagel, Mark A. Anastasio, Umberto Villa:
ProxNF: Neural Field Proximal Training for High-Resolution 4D Dynamic Image Reconstruction. IEEE Trans. Computational Imaging 10: 1368-1383 (2024) - [i20]Linus Seelinger, Anne Reinarz, Mikkel Bue Lykkegaard, Amal Mohammed A. Alghamdi, David Aristoff, Wolfgang Bangerth, Jean Bénézech, Matteo Diez, Kurt Frey, John D. Jakeman, Jakob Sauer Jørgensen, Ki-Tae Kim, Massimiliano Martinelli, Matthew D. Parno, Riccardo Pellegrini, Noemi Petra, Nicolai André Brogaard Riis, Katherine Rosenfeld, Andrea Serani, Lorenzo Tamellini, Umberto Villa, Tim J. Dodwell, Robert Scheichl:
Democratizing Uncertainty Quantification. CoRR abs/2402.13768 (2024) - [i19]Umberto Villa, Thomas O'Leary-Roseberry:
A note on the relationship between PDE-based precision operators and Matérn covariances. CoRR abs/2407.00471 (2024) - [i18]Youzuo Lin, Shihang Feng, James Theiler, Yinpeng Chen, Umberto Villa, Jing Rao, John James Greenhall, Cristian Pantea, Mark A. Anastasio, Brendt Wohlberg:
Physics and Deep Learning in Computational Wave Imaging. CoRR abs/2410.08329 (2024) - [i17]Evan Scope Crafts, Mark A. Anastasio, Umberto Villa:
Optimizing Quantitative Photoacoustic Imaging Systems: The Bayesian Cramér-Rao Bound Approach. CoRR abs/2410.09557 (2024) - 2023
- [j21]Delyan Z. Kalchev, Panayot S. Vassilevski, Umberto Villa:
Parallel Element-Based Algebraic Multigrid for \(\boldsymbol{H}\) (curl) and \(\boldsymbol{H}\) (div) Problems Using the ParELAG Library. SIAM J. Sci. Comput. 45(3): S371-S400 (2023) - [j20]Baoshan Liang, Jingye Tan, Luke Lozenski, David A. Hormuth, Thomas E. Yankeelov, Umberto Villa, Danial Faghihi:
Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth. IEEE Trans. Medical Imaging 42(10): 2865-2875 (2023) - [j19]Weimin Zhou, Umberto Villa, Mark A. Anastasio:
Ideal Observer Computation by Use of Markov-Chain Monte Carlo With Generative Adversarial Networks. IEEE Trans. Medical Imaging 42(12): 3715-3724 (2023) - [j18]Ki-Tae Kim, Umberto Villa, Matthew D. Parno, Youssef M. Marzouk, Omar Ghattas, Noemi Petra:
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. ACM Trans. Math. Softw. 49(2): 17:1-17:31 (2023) - [i16]Baoshan Liang, Luke Lozenski, Umberto Villa, Danial Faghihi:
Technical Note: PDE-constrained Optimization Formulation for Tumor Growth Model Calibration. CoRR abs/2302.06445 (2023) - [i15]Weimin Zhou, Umberto Villa, Mark A. Anastasio:
Ideal Observer Computation by Use of Markov-Chain Monte Carlo with Generative Adversarial Networks. CoRR abs/2304.00433 (2023) - 2022
- [j17]Jeonghun J. Lee, Tan Bui-Thanh, Umberto Villa, Omar Ghattas:
Forward and inverse modeling of fault transmissibility in subsurface flows. Comput. Math. Appl. 128: 354-367 (2022) - [j16]Luke Lozenski, Mark A. Anastasio, Umberto Villa:
A Memory-Efficient Self-Supervised Dynamic Image Reconstruction Method Using Neural Fields. IEEE Trans. Computational Imaging 8: 879-892 (2022) - [c5]Jason L. Granstedt, Fu Li, Umberto Villa, Mark A. Anastasio:
Learned Hotelling observers for use with multi-modal data. Image Perception, Observer Performance, and Technology Assessment 2022 - [i14]Sayantan Bhadra, Umberto Villa, Mark A. Anastasio:
Mining the manifolds of deep generative models for multiple data-consistent solutions of ill-posed tomographic imaging problems. CoRR abs/2202.05311 (2022) - [i13]Thomas O'Leary-Roseberry, Peng Chen, Umberto Villa, Omar Ghattas:
Derivative-Informed Neural Operator: An Efficient Framework for High-Dimensional Parametric Derivative Learning. CoRR abs/2206.10745 (2022) - [i12]Baoshan Liang, Jingye Tan, Luke Lozenski, David A. Hormuth II, Thomas E. Yankeelov, Umberto Villa, Danial Faghihi:
Bayesian Inference of Tissue Heterogeneity for Individualized Prediction of Glioma Growth. CoRR abs/2209.12089 (2022) - 2021
- [j15]Hillary R. Fairbanks, Umberto Villa, Panayot S. Vassilevski:
Multilevel Hierarchical Decomposition of Finite Element White Noise with Application to Multilevel Markov Chain Monte Carlo. SIAM J. Sci. Comput. 43(5): S293-S316 (2021) - [j14]Umberto Villa, Noemi Petra, Omar Ghattas:
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference. ACM Trans. Math. Softw. 47(2): 16:1-16:34 (2021) - [i11]Amal Alghamdi, Marc Andre Hesse, Jingyi Chen, Umberto Villa, Omar Ghattas:
Bayesian Poroelastic Aquifer Characterization from InSAR Surface Deformation Data Part II: Quantifying the Uncertainty. CoRR abs/2102.04577 (2021) - [i10]Luke Lozenski, Umberto Villa:
Consensus ADMM for Inverse Problems Governed by Multiple PDE Models. CoRR abs/2104.13899 (2021) - [i9]Delyan Z. Kalchev, Panayot S. Vassilevski, Umberto Villa:
Parallel Element-based Algebraic Multigrid for H(curl) and H(div) Problems Using the ParELAG Library. CoRR abs/2107.05613 (2021) - [i8]Pedram Maleki, Jingye Tan, Lu An, Massimigliano Di Luigi, Umberto Villa, Chi Zhou, Shenqiang Ren, Danial Faghihi:
A Predictive Multiphase Model of Silica Aerogels for Building Envelope Insulations. CoRR abs/2107.12182 (2021) - [i7]Ki-Tae Kim, Umberto Villa, Matthew D. Parno, Youssef M. Marzouk, Omar Ghattas, Noemi Petra:
hIPPYlib-MUQ: A Bayesian Inference Software Framework for Integration of Data with Complex Predictive Models under Uncertainty. CoRR abs/2112.00713 (2021) - 2020
- [c4]Tao Ge, Umberto Villa, Ulugbek S. Kamilov, Joseph A. O'Sullivan:
Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization. Computational Imaging 2020 - [i6]Hillary R. Fairbanks, Umberto Villa, Panayot S. Vassilevski:
Multilevel Hierarchical Decomposition of Finite Element White Noise with Application to Multilevel Markov Chain Monte Carlo. CoRR abs/2007.14440 (2020) - [i5]Thomas O'Leary-Roseberry, Umberto Villa, Peng Chen, Omar Ghattas:
Derivative-Informed Projected Neural Networks for High-Dimensional Parametric Maps Governed by PDEs. CoRR abs/2011.15110 (2020) - [i4]Jingye Tan, Umberto Villa, Nima Shamsaei, Shuai Shao, Hussein M. Zbib, Danial Faghihi:
A Predictive Discrete-Continuum Multiscale Model of Plasticity With Quantified Uncertainty. CoRR abs/2012.10823 (2020)
2010 – 2019
- 2019
- [j13]Peng Chen, Umberto Villa, Omar Ghattas:
Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty. J. Comput. Phys. 385: 163-186 (2019) - [j12]Boris Kramer, Alexandre Noll Marques, Benjamin Peherstorfer, Umberto Villa, Karen Willcox:
Multifidelity probability estimation via fusion of estimators. J. Comput. Phys. 392: 385-402 (2019) - [i3]Boris Kramer, Alexandre Noll Marques, Benjamin Peherstorfer, Umberto Villa, Karen Willcox:
Multifidelity probability estimation via fusion of estimators. CoRR abs/1905.02679 (2019) - [i2]Umberto Villa, Noemi Petra, Omar Ghattas:
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs; Part I: Deterministic Inversion and Linearized Bayesian Inference. CoRR abs/1909.03948 (2019) - [i1]Tao Ge, Umberto Villa, Ulugbek S. Kamilov, Joseph A. O'Sullivan:
Proximal Newton Methods for X-Ray Imaging with Non-Smooth Regularization. CoRR abs/1912.01738 (2019) - 2018
- [j11]Max la Cour Christensen, Panayot S. Vassilevski, Umberto Villa:
Nonlinear multigrid solvers exploiting AMGe coarse spaces with approximation properties. J. Comput. Appl. Math. 340: 691-708 (2018) - [j10]Umberto Villa, Noemi Petra, Omar Ghattas:
hIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems. J. Open Source Softw. 3(30): 940 (2018) - [j9]Sarah Osborn, Patrick Zulian, Thomas Benson, Umberto Villa, Rolf Krause, Panayot S. Vassilevski:
Scalable hierarchical PDE sampler for generating spatially correlated random fields using nonmatching meshes. Numer. Linear Algebra Appl. 25(3) (2018) - 2017
- [j8]Sofia Guzzetti, Tiziano Passerini, Jaroslaw Slawinski, Umberto Villa, Alessandro Veneziani, Vaidy S. Sunderam:
Platform and algorithm effects on computational fluid dynamics applications in life sciences. Future Gener. Comput. Syst. 67: 382-396 (2017) - [j7]Max la Cour Christensen, Umberto Villa, Allan Peter Engsig-Karup, Panayot S. Vassilevski:
Numerical Multilevel Upscaling for Incompressible Flow in Reservoir Simulation: An Element-Based Algebraic Multigrid (AMGe) Approach. SIAM J. Sci. Comput. 39(1) (2017) - [j6]Nick Alger, Umberto Villa, Tan Bui-Thanh, Omar Ghattas:
A Data Scalable Augmented Lagrangian KKT Preconditioner for Large-Scale Inverse Problems. SIAM J. Sci. Comput. 39(5) (2017) - [j5]Sarah Osborn, Panayot S. Vassilevski, Umberto Villa:
A Multilevel, Hierarchical Sampling Technique for Spatially Correlated Random Fields. SIAM J. Sci. Comput. 39(5) (2017) - 2016
- [j4]Delyan Kalchev, Chak Shing Lee, Umberto Villa, Yalchin Efendiev, Panayot S. Vassilevski:
Upscaling of Mixed Finite Element Discretization Problems by the Spectral AMGe Method. SIAM J. Sci. Comput. 38(5) (2016) - 2014
- [j3]Panayot S. Vassilevski, Umberto Villa:
A Mixed Formulation for the Brinkman Problem. SIAM J. Numer. Anal. 52(1): 258-281 (2014) - [c3]Tiziano Passerini, Jaroslaw Slawinski, Umberto Villa, Vaidy S. Sunderam:
Experiences with Cost and Utility Trade-offs on IaaS Clouds, Grids, and On-Premise Resources. IC2E 2014: 391-396 - 2013
- [j2]Alessandro Veneziani, Umberto Villa:
ALADINS: An ALgebraic splitting time ADaptive solver for the Incompressible Navier-Stokes equations. J. Comput. Phys. 238: 359-375 (2013) - [j1]Panayot S. Vassilevski, Umberto Villa:
A Block-Diagonal Algebraic Multigrid Preconditioner for the Brinkman Problem. SIAM J. Sci. Comput. 35(5) (2013) - [c2]Jaroslaw Slawinski, Umberto Villa, Tiziano Passerini, Alessandro Veneziani, Vaidy S. Sunderam:
Issues in Communication Heterogeneity for Message-Passing Concurrent Computing. IPDPS Workshops 2013: 93-102 - 2012
- [c1]Jaroslaw Slawinski, Tiziano Passerini, Umberto Villa, Alessandro Veneziani, Vaidy S. Sunderam:
Experiences with Target-Platform Heterogeneity in Clouds, Grids, and On-Premises Resources. IPDPS Workshops 2012: 41-52
Coauthor Index
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