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Ushnish Sengupta
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Year
Loop Motion in Triosephosphate Isomerase is not a Simple Open and Shut Case
Q Liao, Y Kulkarni, U Sengupta, D Petrovic, AJ Mulholland, ...
Journal of the American Chemical Society, 2018
592018
Automated Markov state models for molecular dynamics simulations of aggregation and self-assembly
U Sengupta, M Carballo-Pacheco, B Strodel
The Journal of Chemical Physics 150 (11), 115101, 2019
402019
Markov models for the elucidation of allosteric regulation
U Sengupta, B Strodel
Philosophical Transactions of the Royal Society B 373 (Allostery and …, 2018
232018
Ensembling Geophysical Models with Bayesian Neural Networks
U Sengupta, M Amos, JS Hosking, CE Rasmussen, M Juniper, PJ Young
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
152020
Early Detection of Thermoacoustic Instabilities in a Cryogenic Rocket Thrust Chamber using Combustion Noise Features and Machine Learning
G Waxenegger-Wilfing, U Sengupta, J Martin, W Armbruster, J Hardi, ...
Chaos, 2020
142020
Bayesian machine learning for the prognosis of combustion instabilities from noise
U Sengupta, CE Rasmussen, MP Juniper
Journal of Engineering for Gas Turbines and Power 143 (7), 2021
132021
Data assimilation using heteroscedastic Bayesian neural network ensembles for reduced-order flame models
ML Croci, U Sengupta, MP Juniper
Computational Science–ICCS 2021: 21st International Conference, Krakow …, 2021
7*2021
Modelling an Air-Conditioner Fire in a Seminar Room using FDS
U Sengupta, AK Das
National Conference on Fire Research and Engineering, IIT Roorkee, 2014
62014
Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles
U Sengupta, M Croci, MP Juniper
3rd Workshop on Machine Learning and the Physical Sciences, NeurIPS 2020, 2020
42020
Reducing Uncertainty in the Onset of Combustion Instabilities using Dynamic Pressure Information and Bayesian Neural Networks
M McCartney, U Sengupta, M Juniper
Journal of Engineering for Gas Turbines and Power, 2022
22022
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning
U Sengupta, G Waxenegger-Wilfing, J Martin, J Hardi, MP Juniper
International Journal of Spray and Combustion Dynamics, 2021
22021
Bayesian inference in physics-based nonlinear flame models
ML Croci, U Sengupta, MP Juniper
NeurIPS 2021 Workshop on Deep Learning and Inverse Problems, 2021
12021
Avoiding high-frequency thermoacoustic instabilities in liquid propellant rocket engines using Bayesian deep learning
U Sengupta, G Waxenegger-Wilfing, J Martin, J Hardi, M Juniper
APS Division of Fluid Dynamics Meeting Abstracts, R01. 026, 2020
12020
Time-Accurate Calibration of a Thermoacoustic Model on Experimental Images of a Forced Premixed Flame
H Yu, U Sengupta, M Juniper, L Magri
72nd Annual Meeting of the APS Division of Fluid Dynamics, P06. 008, 2019
12019
Physics-informed Deep Learning for Flow Modelling and Aerodynamic Optimization
Y Sun, U Sengupta, M Juniper
2022 IEEE Symposium Series on Computational Intelligence (SSCI), 1149-1155, 2022
2022
Physics-informed Deep Learning for simultaneous Surrogate Modelling and PDE-constrained Optimization
Y Sun, U Sengupta, M Juniper
Journal of Computational Science, 2022
2022
Thermoacoustic stabilization of combustors with gradient-augmented Bayesian optimization and adjoint models
U Sengupta, M Juniper
International Journal of Spray and Combustion Dynamics, 2022
2022
Bayesian parameter inference of a vortically perturbed flame model for the prediction of thermoacoustic instability
ML Croci, JV Vasanth, U Sengupta, E Ekici, MP Juniper
NeurIPS 2022 AI for Science: Progress and Promises, 2022
2022
A continuous vertically resolved ozone dataset from the fusion of chemistry climate models with observations using a Bayesian neural network
M Amos, U Sengupta, P Young, JS Hosking
EarthArXiv, 2021
2021
Fusing model ensembles and observations together with Bayesian neural networks
M Amos, U Sengupta, S Hosking, P Young
EGU General Assembly Conference Abstracts, EGU21-11905, 2021
2021
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