Ilias Bilionis

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 37

Top Topics

Variational Inference

Systems Engineering

Information Revelation

Top Venues

J. Comput. Phys.

Comput. Aided Civ. Infrastructure Eng.

Publications

Sharmila Karumuri, Ilias Bilionis
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guides. J. Comput. Phys. 511 (2024)
Kairui Hao, Ilias Bilionis
An information field theory approach to Bayesian state and parameter estimation in dynamical systems. J. Comput. Phys. 512 (2024)
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 (2024)
Alex Alberts, Ilias Bilionis
Physics-informed information field theory for modeling physical systems with uncertainty quantification. J. Comput. Phys. 486 (2023)
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) (2023)
Sharmila Karumuri, Ilias Bilionis
Learning to solve Bayesian inverse problems: An amortized variational inference approach. CoRR (2023)
Vahidullah Tac, Manuel K. Rausch, Ilias Bilionis, Francisco Sahli Costabal, Adrian Buganza Tepole
Generative Hyperelasticity with Physics-Informed Probabilistic Diffusion Fields. CoRR (2023)
Alex Alberts, Ilias Bilionis
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification. CoRR (2023)
Kairui Hao, Ilias Bilionis
An information field theory approach to Bayesian state and parameter estimation in dynamical systems. CoRR (2023)
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)
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) (2022)
Shrenik Zinage, Suyash Jadhav, Yifei Zhou, Ilias Bilionis, Peter H. Meckl
Data Driven Modeling of Turbocharger Turbine using Koopman Operator. CoRR (2022)
Andrés Beltrán-Pulido, Ilias Bilionis, Dionysios Aliprantis
Physics-informed neural networks for solving parametric magnetostatic problems. CoRR (2022)
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 (2021)
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)
Kolawole Ogunsina, Ilias Bilionis, Daniel DeLaurentis
Exploratory Data Analysis for Airline Disruption Management. CoRR (2021)
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)
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) (2020)
Salar Safarkhani, Ilias Bilionis, Jitesh H. Panchal
Modeling the System Acquisition Using Deep Reinforcement Learning. IEEE Access 8 (2020)
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) (2020)
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 (2020)
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) (2020)
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) (2020)
Nimish Awalgaonkar, Ilias Bilionis, Xiaoqi Liu, Panagiota Karava, Athanasios Tzempelikos
Learning Personalized Thermal Preferences via Bayesian Active Learning with Unimodality Constraints. CoRR (2019)
Ali Lenjani, Ilias Bilionis, Shirley Dyke, Chul Min Yeum, Ricardo Monteiro
A Resilience-based Method for Prioritizing Post-event Building Inspections. CoRR (2019)
Salar Safarkhani, Vikranth Reddy Kattakuri, Ilias Bilionis, Jitesh H. Panchal
A Principal-Agent Model of Systems Engineering Processes with Application to Satellite Design. CoRR (2019)
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 (2019)
Chul Min Yeum, Ali Lenjani, Shirley J. Dyke, Ilias Bilionis
Automated Detection of Pre-Disaster Building Images from Google Street View. CoRR (2019)
Ali Lenjani, Chul Min Yeum, Shirley Dyke, Ilias Bilionis
Automated Building Image Extraction from 360-degree Panoramas for Post-Disaster Evaluation. CoRR (2019)
Simon Scheidegger, Ilias Bilionis
Machine learning for high-dimensional dynamic stochastic economies. J. Comput. Sci. 33 (2019)
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 (2019)
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 (2019)
Rohit Tripathy, Ilias Bilionis
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification. CoRR (2018)
Rohit Tripathy, Ilias Bilionis
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification. J. Comput. Phys. 375 (2018)
Adam Dachowicz, Siva Chaitanya Chaduvula, Mikhail J. Atallah, Ilias Bilionis, Jitesh H. Panchal
Strategic information revelation in collaborative design. Adv. Eng. Informatics 36 (2018)
Piyush Pandita, Ilias Bilionis, Jitesh H. Panchal
Deriving Information Acquisition Criteria For Sequentially Inferring The Expected Value Of A Black-Box Function. CoRR (2018)
Rohit Tripathy, Ilias Bilionis, Marcial Gonzalez
Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation. J. Comput. Phys. 321 (2016)
Peng Chen, Nicholas Zabaras, Ilias Bilionis
Uncertainty propagation using infinite mixture of Gaussian processes and variational Bayesian inference. J. Comput. Phys. 284 (2015)
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 (2013)
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) (2012)
Ilias Bilionis, Nicholas Zabaras
Multi-output local Gaussian process regression: Applications to uncertainty quantification. J. Comput. Phys. 231 (17) (2012)
Ilias Bilionis, Nicholas Zabaras
Multidimensional Adaptive Relevance Vector Machines for Uncertainty Quantification. SIAM J. Sci. Comput. 34 (6) (2012)