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ORCIDIlias Bilionis
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2020 – today
- 2024
[j23]Amir Behjat, Xiaoyu Liu
, Oscar Forero, Roman Ibrahimov, Shirley Dyke, Ilias Bilionis, Julio Alfonso Ramirez, Dawn Whitaker:
A computational framework for making early design decisions in deep space habitats. Adv. Eng. Softw. 195: 103690 (2024)- [j22]Sharmila Karumuri, Ilias Bilionis:
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides. J. Comput. Phys. 511: 113117 (2024) - [j21]Kairui Hao, Ilias Bilionis:
An information field theory approach to Bayesian state and parameter estimation in dynamical systems. J. Comput. Phys. 512: 113139 (2024) - [i20]Shrenik Zinage, Ilias Bilionis, Peter H. Meckl:
A Causal Graph-Enhanced Gaussian Process Regression for Modeling Engine-out NOx. CoRR abs/2410.18424 (2024) - 2023
- [j20]Xiaoyu Liu, Shirley J. Dyke, Ali Lenjani, Ilias Bilionis, Xin Zhang, Jongseong Choi:
Automated image localization to support rapid building reconnaissance in a large-scale area. Comput. Aided Civ. Infrastructure Eng. 38(1): 3-25 (2023) - [j19]Atharva Hans, Ashish M. Chaudhari, Ilias Bilionis, Jitesh H. Panchal:
A Bayesian Hierarchical Model for Extracting Individuals' Theory-Based Causal Knowledge. J. Comput. Inf. Sci. Eng. 23(3) (2023) - [j18]Alex Alberts, Ilias Bilionis:
Physics-informed information field theory for modeling physical systems with uncertainty quantification. J. Comput. Phys. 486: 112100 (2023) - [i19]Alex Alberts, Ilias Bilionis:
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification. CoRR abs/2301.07609 (2023) - [i18]Sharmila Karumuri, Ilias Bilionis:
Learning to solve Bayesian inverse problems: An amortized variational inference approach. CoRR abs/2305.20004 (2023) - [i17]Kairui Hao, Ilias Bilionis:
An information field theory approach to Bayesian state and parameter estimation in dynamical systems. CoRR abs/2306.02150 (2023) - [i16]Vahidullah Tac, Manuel K. Rausch, Ilias Bilionis, Francisco Sahli Costabal, Adrian Buganza Tepole:
Generative Hyperelasticity with Physics-Informed Probabilistic Diffusion Fields. CoRR abs/2310.03745 (2023) - 2022
- [j17]Jongseong Choi, Ju An Park, Shirley J. Dyke, Chul Min Yeum, Xiaoyu Liu, Ali Lenjani, Ilias Bilionis:
Similarity learning to enable building searches in post-event image data. Comput. Aided Civ. Infrastructure Eng. 37(2): 261-275 (2022) - [i15]Andrés Beltrán-Pulido, Ilias Bilionis, Dionysios Aliprantis:
Physics-informed neural networks for solving parametric magnetostatic problems. CoRR abs/2202.04041 (2022) - [i14]Shrenik Zinage, Suyash Jadhav, Yifei Zhou, Ilias Bilionis, Peter H. Meckl:
Data Driven Modeling of Turbocharger Turbine using Koopman Operator. CoRR abs/2204.10421 (2022) - 2021
- [c1]Ilias Bilionis, Georgios K. Apostolidis, Vasileios S. Charisis, Christos N. Liatsos, Leontios J. Hadjileontiadis:
Non-invasive Detection of Bowel Sounds in Real-life Settings Using Spectrogram Zeros and Autoencoding. EMBC 2021: 915-919 - [i13]Kolawole Ogunsina, Ilias Bilionis, Daniel DeLaurentis:
Exploratory Data Analysis for Airline Disruption Management. CoRR abs/2102.03711 (2021) - [i12]Marios Papamichalis, Abhishek Ray, Ilias Bilionis, Karthik N. Kannan, Rajiv Krishnamurthy:
Bayesian Model Averaging for Data Driven Decision Making when Causality is Partially Known. CoRR abs/2105.05395 (2021) - 2020
- [j16]Salar Safarkhani, Ilias Bilionis, Jitesh H. Panchal:
Modeling the System Acquisition Using Deep Reinforcement Learning. IEEE Access 8: 124894-124904 (2020) - [j15]Ali Lenjani, Chul Min Yeum, Shirley Dyke, Ilias Bilionis:
Automated building image extraction from 360° panoramas for postdisaster evaluation. Comput. Aided Civ. Infrastructure Eng. 35(3): 241-257 (2020) - [j14]Alex D. Casey, Steven F. Son, Ilias Bilionis, Brian C. Barnes:
Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks. J. Chem. Inf. Model. 60(10): 4457-4473 (2020) - [j13]Sharmila Karumuri, Rohit Tripathy, Ilias Bilionis, Jitesh H. Panchal:
Simulator-free solution of high-dimensional stochastic elliptic partial differential equations using deep neural networks. J. Comput. Phys. 404 (2020) - [j12]Xiaoyu Liu, Shirley J. Dyke, Chul Min Yeum, Ilias Bilionis, Ali Lenjani, Jongseong Choi:
Automated Indoor Image Localization to Support a Post-Event Building Assessment. Sensors 20(6): 1610 (2020) - [j11]Salar Safarkhani, Ilias Bilionis, Jitesh H. Panchal:
Toward a Theory of Systems Engineering Processes: A Principal-Agent Model of a One-Shot, Shallow Process. IEEE Syst. J. 14(3): 3277-3288 (2020) - [i11]Casey Stowers, Taeksang Lee, Ilias Bilionis, Arun Gosain, Adrian Buganza Tepole:
Improving Reconstructive Surgery Design using Gaussian Process Surrogates to Capture Material Behavior Uncertainty. CoRR abs/2010.02800 (2020)
2010 – 2019
- 2019
- [j10]Simon Scheidegger, Ilias Bilionis:
Machine learning for high-dimensional dynamic stochastic economies. J. Comput. Sci. 33: 68-82 (2019) - [i10]Chul Min Yeum, Ali Lenjani, Shirley J. Dyke, Ilias Bilionis:
Automated Detection of Pre-Disaster Building Images from Google Street View. CoRR abs/1902.10816 (2019) - [i9]Salar Safarkhani, Vikranth Reddy Kattakuri, Ilias Bilionis, Jitesh H. Panchal:
A Principal-Agent Model of Systems Engineering Processes with Application to Satellite Design. CoRR abs/1903.06979 (2019) - [i8]Nimish Awalgaonkar, Ilias Bilionis, Xiaoqi Liu, Panagiota Karava, Athanasios Tzempelikos:
Learning Personalized Thermal Preferences via Bayesian Active Learning with Unimodality Constraints. CoRR abs/1903.09094 (2019) - [i7]Salar Safarkhani, Ilias Bilionis, Jitesh H. Panchal:
Towards a Theory of Systems Engineering Processes: A Principal-Agent Model of a One-Shot, Shallow Process. CoRR abs/1903.12086 (2019) - [i6]Ali Lenjani, Chul Min Yeum, Shirley Dyke, Ilias Bilionis:
Automated Building Image Extraction from 360-degree Panoramas for Post-Disaster Evaluation. CoRR abs/1905.01524 (2019) - [i5]Ali Lenjani, Ilias Bilionis, Shirley Dyke, Chul Min Yeum, Ricardo Monteiro:
A Resilience-based Method for Prioritizing Post-event Building Inspections. CoRR abs/1906.12319 (2019) - [i4]Ali Lenjani, Shirley J. Dyke, Ilias Bilionis, Chul Min Yeum, Kenzo Kamiya, Jongseong Choi, Xiaoyu Liu, Arindam G. Chowdhury:
Towards fully automated post-event data collection and analysis: pre-event and post-event information fusion. CoRR abs/1907.05285 (2019) - [i3]Piyush Pandita, Nimish Awalgaonkar, Ilias Bilionis, Jitesh H. Panchal:
Learning Arbitrary Quantities of Interest from Expensive Black-Box Functions through Bayesian Sequential Optimal Design. CoRR abs/1912.07366 (2019) - 2018
- [j9]Adam Dachowicz, Siva Chaitanya Chaduvula, Mikhail J. Atallah, Ilias Bilionis, Jitesh H. Panchal:
Strategic information revelation in collaborative design. Adv. Eng. Informatics 36: 242-253 (2018) - [j8]Rohit K. Tripathy, Ilias Bilionis:
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification. J. Comput. Phys. 375: 565-588 (2018) - [i2]Rohit K. Tripathy, Ilias Bilionis:
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification. CoRR abs/1802.00850 (2018) - [i1]Piyush Pandita, Ilias Bilionis, Jitesh H. Panchal:
Deriving Information Acquisition Criteria For Sequentially Inferring The Expected Value Of A Black-Box Function. CoRR abs/1807.09979 (2018) - 2016
- [j7]Rohit Tripathy, Ilias Bilionis, Marcial Gonzalez:
Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation. J. Comput. Phys. 321: 191-223 (2016) - 2015
- [j6]Peng Chen, Nicholas Zabaras, Ilias Bilionis:
Uncertainty propagation using infinite mixture of Gaussian processes and variational Bayesian inference. J. Comput. Phys. 284: 291-333 (2015) - 2013
- [j5]Ilias Bilionis, Nicholas Zabaras, Bledar A. Konomi, Guang Lin:
Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification. J. Comput. Phys. 241: 212-239 (2013) - 2012
- [j4]Ilias Bilionis, Phaedon-Stelios Koutsourelakis:
Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations. J. Comput. Phys. 231(9): 3849-3870 (2012) - [j3]Ilias Bilionis, Nicholas Zabaras:
Multi-output local Gaussian process regression: Applications to uncertainty quantification. J. Comput. Phys. 231(17): 5718-5746 (2012) - [j2]Ilias Bilionis, Nicholas Zabaras:
Multidimensional Adaptive Relevance Vector Machines for Uncertainty Quantification. SIAM J. Sci. Comput. 34(6) (2012) - 2011
- [j1]Phaedon-Stelios Koutsourelakis, Elias Bilionis:
Scalable Bayesian Reduced-Order Models for Simulating High-Dimensional Multiscale Dynamical Systems. Multiscale Model. Simul. 9(1): 449-485 (2011)
Coauthor Index
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