| Bayesian Machine Learning Approach to the Quantification of Uncertainties on Ab Initio Potential Energy Surfaces S Venturi, RL Jaffe, M Panesi The Journal of Physical Chemistry A 124 (25), 5129–5146, 2020 | 54 | 2020 |
| Data-Inspired and Physics-Driven Model Reduction for Dissociation: Application to the O2+O System S Venturi, MP Sharma, B Lopez, M Panesi The Journal of Physical Chemistry A 124 (41), 8359-8372, 2020 | 42 | 2020 |
| Comparison of Potential Energy Surface and Computed Rate Coefficients for Dissociation RL Jaffe, M Grover, S Venturi, DW Schwenke, P Valentini, ... Journal of thermophysics and heat transfer 32 (4), 869-881, 2018 | 40 | 2018 |
| SVD Perspectives for Augmenting DeepONet Flexibility and Interpretability S Venturi, T Casey Computer Methods in Applied Mechanics and Engineering 403, 115718, 2023 | 30 | 2023 |
| Comparison of quantum mechanical and empirical potential energy surfaces and computed rate coefficients for N2 dissociation RL Jaffe, DW Schwenke, M Grover, P Valentini, TE Schwartzentruber, ... 54th AIAA Aerospace Sciences Meeting, 0503, 2016 | 27 | 2016 |
| Rovibrational-Specific QCT and Master Equation Study on N2(X1Σg+) + O(3P) and NO(X2Π) + N(4S) Systems in High-Energy Collisions SM Jo, S Venturi, MP Sharma, A Munafò, M Panesi The Journal of Physical Chemistry A 126 (21), 3273-3290, 2022 | 20 | 2022 |
| Application of DeepOnet to model inelastic scattering probabilities in air mixtures M Sharma Priyadarshini, S Venturi, M Panesi AIAA Aviation 2021 Forum, 3144, 2021 | 15 | 2021 |
| Calibration and uncertainty quantification of VISTA Ablator material database using Bayesian inference P Rostkowski, S Venturi, M Panesi, A Omidy, H Weng, A Martin Journal of Thermophysics and Heat Transfer 33 (2), 356-369, 2019 | 15 | 2019 |
| Effects of Ab-Initio Potential Energy Surfaces on O2-O Non-Equilibrium Kinetics S Venturi, M Sharma Priyadarshini, A Racca, M Panesi AIAA Aviation 2019, 2019 | 11 | 2019 |
| A Machine Learning Framework for the Quantification of the Uncertainties Associated with Ab-Initio Based Modeling of Non-Equilibrium Flows S Venturi, M Sharma Priyadarshini, M Panesi AIAA Scitech 2019 Forum, 0788, 2019 | 10 | 2019 |
| Towards efficient simulations of non-equilibrium chemistry in hypersonic flows: a physics-informed neural network framework I Zanardi, S Venturi, M Panesi AIAA SCITECH 2022 Forum, 1639, 2022 | 9 | 2022 |
| Physics-based stochastic framework for the quantification of uncertainty in non-equilibrium hypersonic flows S Venturi Politecnico di Milano, 2014 | 9 | 2014 |
| Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows I Zanardi, S Venturi, M Panesi Scientific reports 13 (1), 15497, 2023 | 8 | 2023 |
| Rovibrational internal energy transfer and dissociation of high-temperature oxygen mixture SM Jo, S Venturi, JG Kim, M Panesi The Journal of Chemical Physics 158 (6), 2023 | 7 | 2023 |
| State-to-state and reduced-order models for recombination and energy transfer in aerothermal environments A Munafò, S Venturi, RL Macdonald, M Panesi 54th AIAA Aerospace Sciences Meeting, 0505, 2016 | 7 | 2016 |
| Machine Learning and Uncertainty Quantification Framework for Predictive Ab Initio Hypersonics S Venturi University of Illinois at Urbana-Champaign, 2021 | 6 | 2021 |
| Reduced-order modeling for non-equilibrium air flows A Munafò, S Venturi, M Sharma Priyadarshini, M Panesi AIAA Scitech 2020 Forum, 1226, 2020 | 5 | 2020 |
| Investigating CO dissociation by means of coarse grained ab-initio rate constants S Venturi, M Panesi 2018 AIAA Aerospace Sciences Meeting, 1232, 2018 | 5 | 2018 |
| Comprehensive study of HCN: Potential energy surfaces, state-to-state kinetics, and master equation analysis MS Priyadarshini, SM Jo, S Venturi, DW Schwenke, RL Jaffe, M Panesi The Journal of Physical Chemistry A 126 (44), 8249-8265, 2022 | 4 | 2022 |
| An uncertainty-aware strategy for plasma mechanism reduction with directed weighted graphs S Venturi, W Yang, I Kaganovich, T Casey Physics of Plasmas 30 (4), 2023 | 3 | 2023 |
Marco PanesiProfessor of Aerospace Engineering, University of Illinois at Urbana-Champaign在 illinois.edu 的电子邮件经过验证
