Ilias Bilionis
Orcid: 0000-0002-5266-105X
According to our database1,
Ilias Bilionis
authored at least 40 papers
between 2011 and 2024.
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Bibliography
2024
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides.
J. Comput. Phys., 2024
An information field theory approach to Bayesian state and parameter estimation in dynamical systems.
J. Comput. Phys., 2024
Adv. Eng. Softw., 2024
2023
A Bayesian Hierarchical Model for Extracting Individuals' Theory-Based Causal Knowledge.
J. Comput. Inf. Sci. Eng., June, 2023
Automated image localization to support rapid building reconnaissance in a large-scale area.
Comput. Aided Civ. Infrastructure Eng., January, 2023
Physics-informed information field theory for modeling physical systems with uncertainty quantification.
J. Comput. Phys., 2023
CoRR, 2023
Learning to solve Bayesian inverse problems: An amortized variational inference approach.
CoRR, 2023
2022
CoRR, 2022
Comput. Aided Civ. Infrastructure Eng., 2022
2021
Bayesian Model Averaging for Data Driven Decision Making when Causality is Partially Known.
CoRR, 2021
Non-invasive Detection of Bowel Sounds in Real-life Settings Using Spectrogram Zeros and Autoencoding.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
2020
Toward a Theory of Systems Engineering Processes: A Principal-Agent Model of a One-Shot, Shallow Process.
IEEE Syst. J., 2020
Sensors, 2020
Simulator-free solution of high-dimensional stochastic elliptic partial differential equations using deep neural networks.
J. Comput. Phys., 2020
Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks.
J. Chem. Inf. Model., 2020
Improving Reconstructive Surgery Design using Gaussian Process Surrogates to Capture Material Behavior Uncertainty.
CoRR, 2020
Comput. Aided Civ. Infrastructure Eng., 2020
2019
J. Comput. Sci., 2019
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design.
CoRR, 2019
Towards fully automated post-event data collection and analysis: pre-event and post-event information fusion.
CoRR, 2019
CoRR, 2019
Automated Building Image Extraction from 360-degree Panoramas for Post-Disaster Evaluation.
CoRR, 2019
Towards a Theory of Systems Engineering Processes: A Principal-Agent Model of a One-Shot, Shallow Process.
CoRR, 2019
Learning Personalized Thermal Preferences via Bayesian Active Learning with Unimodality Constraints.
CoRR, 2019
A Principal-Agent Model of Systems Engineering Processes with Application to Satellite Design.
CoRR, 2019
CoRR, 2019
2018
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification.
J. Comput. Phys., 2018
Deriving Information Acquisition Criteria For Sequentially Inferring The Expected Value Of A Black-Box Function.
CoRR, 2018
Adv. Eng. Informatics, 2018
2016
Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation.
J. Comput. Phys., 2016
2015
Uncertainty propagation using infinite mixture of Gaussian processes and variational Bayesian inference.
J. Comput. Phys., 2015
2013
Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification.
J. Comput. Phys., 2013
2012
SIAM J. Sci. Comput., 2012
Multi-output local Gaussian process regression: Applications to uncertainty quantification.
J. Comput. Phys., 2012
Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations.
J. Comput. Phys., 2012
2011
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems.
Multiscale Model. Simul., 2011