Ushnish Sengupta
Title
Cited by
Cited by
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
372018
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
252019
Markov models for the elucidation of allosteric regulation
U Sengupta, B Strodel
Philosophical Transactions of the Royal Society B 373 (Allostery and …, 2018
142018
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), 071001, 2021
72021
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
52014
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
42020
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
32020
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
22020
Reducing Uncertainty in the Onset of Combustion Instabilities using Dynamic Pressure Information and Bayesian Neural Networks
M McCartney, U Sengupta, M Juniper
ASME Turbo Expo 2021, 2021
12021
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
Data Assimilation Using Heteroscedastic Bayesian Neural Network Ensembles for Reduced-Order Flame Models
ML Croci, U Sengupta, MP Juniper
International Conference on Computational Science, 408-419, 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
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning
U Sengupta, G Waxenegger-Wilfing, J Martin, J Hardi, MP Juniper
2021
Simultaneous boundary shape estimation and velocity field de-noising in Magnetic Resonance Velocimetry using Physics-informed Neural Networks
U Sengupta, A Kontogiannis, MP Juniper
2021
Bayesian Neural Networks for Assimilation of Experimental Data into a G-equation Flame Model
M Croci, U Sengupta, M Juniper
APS Division of Fluid Dynamics Meeting Abstracts, P04. 004, 2020
2020
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
2020
Markov state models of protein aggregation
M Carballo-Pacheco, U Sengupta, B Strodel
EUROPEAN BIOPHYSICS JOURNAL WITH BIOPHYSICS LETTERS 46, S209-S209, 2017
2017
Application of automatic differentiation to molecular dynamics
L GULLÓN, N CHHABRA, U SENGUPTA
2017
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Articles 1–18