Ilias Bilionis

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Panagiota KaravaProfessor of Civil Engineering, Purdue UniversityVerifisert e-postadresse på purdue.edu
Jitesh H. PanchalSchool of Mechanical Engineering, Purdue University, West Lafayette, INVerifisert e-postadresse på purdue.edu
Nicholas ZabarasProfessor, Cornell UniversityVerifisert e-postadresse på nd.edu
Athanasios TzempelikosProfessor of Civil Engineering, Purdue UniversityVerifisert e-postadresse på purdue.edu
Shirley J. DykeCoates Professor of Mechanical Eng, Professor of Civil and Construction Eng, Purdue UniversityVerifisert e-postadresse på purdue.edu
Seungjae LeeUniversity of TorontoVerifisert e-postadresse på utoronto.ca
Rohit TripathyThe Jackson LaboratoryVerifisert e-postadresse på jax.org
Piyush PanditaStaff Engineer, GE AerospaceVerifisert e-postadresse på ge.com
Nimish AwalgaonkarData Science Consultant, ZS AssociatesVerifisert e-postadresse på zs.com
Ali LenjaniStanford UniversityVerifisert e-postadresse på stanford.edu
Adrián Buganza TepolePurdue UniversityVerifisert e-postadresse på purdue.edu
Chul Min YeumUniversity of WaterlooVerifisert e-postadresse på uwaterloo.ca
Sharmila KarumuriPhD, Purdue UniversityVerifisert e-postadresse på purdue.edu
Seyed Amir SadeghiPurdue UniversityVerifisert e-postadresse på purdue.edu
Jie XiongNRELVerifisert e-postadresse på nrel.gov
Ashish M. ChaudhariData Scientist, Philips Research North AmericaVerifisert e-postadresse på mit.edu
Atharva HansPurdue UniversityVerifisert e-postadresse på purdue.edu
Taeksang LeeAssistant Professor of Mechanical Engineering, Myongji UniversityVerifisert e-postadresse på mju.ac.kr
James E. BraunPurdue UniversityVerifisert e-postadresse på purdue.edu
Marcial GonzalezSchool of Mechanical Engineering, Ray W. Herrick Laboratories, Purdue UniversityVerifisert e-postadresse på purdue.edu

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Ilias Bilionis

Professor, Mechanical Engineering, Purdue University

Verifisert e-postadresse på purdue.edu - Startside

Scientific Machine Learning Uncertainty Quantification


Tittel Sorter etter sitater Sorter etter år Sorter etter tittel	Sitert av Sitert av	År
Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification RK Tripathy, I Bilionis Journal of computational physics 375, 565-588, 2018	507	2018
Gaussian processes with built-in dimensionality reduction: Applications to high-dimensional uncertainty propagation R Tripathy, I Bilionis, M Gonzalez Journal of Computational Physics 321, 191-223, 2016	213	2016
Multi-output separable Gaussian process: Towards an efficient, fully Bayesian paradigm for uncertainty quantification I Bilionis, N Zabaras, BA Konomi, G Lin Journal of Computational Physics 241, 212-239, 2013	204	2013
Multi-output local Gaussian process regression: Applications to uncertainty quantification I Bilionis, N Zabaras Journal of Computational Physics 231 (17), 5718-5746, 2012	195	2012
Simulator-free solution of high-dimensional stochastic elliptic partial differential equations using deep neural networks S Karumuri, R Tripathy, I Bilionis, J Panchal Journal of Computational Physics 404, 109120, 2020	161	2020
A Bayesian approach for probabilistic classification and inference of occupant thermal preferences in office buildings S Lee, I Bilionis, P Karava, A Tzempelikos Building and Environment 118, 323-343, 2017	126	2017
Inference of thermal preference profiles for personalized thermal environments with actual building occupants S Lee, P Karava, A Tzempelikos, I Bilionis Building and Environment 148, 714-729, 2019	83	2019
Machine learning for high-dimensional dynamic stochastic economies S Scheidegger, I Bilionis Journal of Computational Science 33, 68-82, 2019	81	2019
Solution of inverse problems with limited forward solver evaluations: a Bayesian perspective I Bilionis, N Zabaras Inverse Problems 30 (1), 015004, 2013	79	2013
Implementation of a self-tuned HVAC controller to satisfy occupant thermal preferences and optimize energy use S Lee, J Joe, P Karava, I Bilionis, A Tzempelikos Energy and Buildings 194, 301-316, 2019	70	2019
Uncertainty propagation using infinite mixture of Gaussian processes and variational Bayesian inference P Chen, N Zabaras, I Bilionis Journal of computational physics 284, 291-333, 2015	62	2015
A stochastic optimization approach to coarse-graining using a relative-entropy framework I Bilionis, N Zabaras The Journal of chemical physics 138 (4), 2013	59	2013
Free energy computations by minimization of Kullback–Leibler divergence: An efficient adaptive biasing potential method for sparse representations I Bilionis, PS Koutsourelakis Journal of Computational Physics 231 (9), 3849-3870, 2012	58	2012
Propagation of uncertainty in the mechanical and biological response of growing tissues using multi-fidelity Gaussian process regression T Lee, I Bilionis, AB Tepole Computer methods in applied mechanics and engineering 359, 112724, 2020	56	2020
Quantifying the impact of domain knowledge and problem framing on sequential decisions in engineering design M Shergadwala, I Bilionis, KN Kannan, JH Panchal Journal of Mechanical Design 140 (10), 101402, 2018	56	2018
A personalized daylighting control approach to dynamically optimize visual satisfaction and lighting energy use J Xiong, A Tzempelikos, I Bilionis, P Karava Energy and Buildings 193, 111-126, 2019	53	2019
Automated building image extraction from 360 panoramas for postdisaster evaluation A Lenjani, CM Yeum, S Dyke, I Bilionis Computer‐Aided Civil and Infrastructure Engineering 35 (3), 241-257, 2020	51	2020
Prediction of energetic material properties from electronic structure using 3D convolutional neural networks AD Casey, SF Son, I Bilionis, BC Barnes Journal of Chemical Information and Modeling 60 (10), 4457-4473, 2020	50	2020
Process optimization of graphene growth in a roll-to-roll plasma CVD system MA Alrefae, A Kumar, P Pandita, A Candadai, I Bilionis, TS Fisher Aip Advances 7 (11), 2017	46	2017
Bayesian uncertainty propagation using Gaussian processes I Bilionis, N Zabaras Handbook of uncertainty quantification, 1-45, 2016	44	2016

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