| 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 | 84 | 2018 |
| 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 | 57 | 2019 |
| Physics-informed Deep Learning for Simultaneous Surrogate Modelling and PDE-constrained Optimization of an airfoil geometry Y Sun, U Sengupta, M Juniper Computer Methods in Applied Mechanics and Engineering, 2023 | 31 | 2023 |
| 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 | 30 | 2020 |
| Markov models for the elucidation of allosteric regulation U Sengupta, B Strodel Philosophical Transactions of the Royal Society B 373 (Allostery and …, 2018 | 28 | 2018 |
| 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 | 25 | 2020 |
| 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 | 21 | 2021 |
| 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 | 10* | 2021 |
| 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 | 5 | 2022 |
| 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 | 5 | 2021 |
| 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 | 5 | 2020 |
| 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 | 5 | 2014 |
| Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling U Sengupta, C Jao, A Bernacchia, S Vakili, D Shiu IEEE Global Communications Conference (GLOBECOM), 2023 | 4 | 2023 |
| Physics-informed Deep Learning for simultaneous Surrogate Modelling and PDE-constrained Optimization Y Sun, U Sengupta, M Juniper Bulletin of the American Physical Society, 2022 | 4 | 2022 |
| Algorithmic Culture: How Big Data and Artificial Intelligence are Transforming Everyday Life JS Beatty, RS Chakraborty, RP Gal, AK Girard, J MacDevitt, U Sengupta Lexington Books, 2020 | 4 | 2020 |
| Thermoacoustic stabilization of combustors with gradient-augmented Bayesian optimization and adjoint models U Sengupta, M Juniper International Journal of Spray and Combustion Dynamics, 2022 | 3 | 2022 |
| Bayesian inference in physics-based nonlinear flame models ML Croci, U Sengupta, MP Juniper NeurIPS 2021 Workshop on Deep Learning and Inverse Problems, 2021 | 3 | 2021 |
| 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 | 2 | 2021 |
| 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 | 1 | 2022 |
| Real-time parameter inference of nonlinear bluff-body-stabilized flame models using Bayesian neural network ensembles ML Croci, U Sengupta, MP Juniper SoTiC 2021 - Symposium on Thermoacoustics in Combustion: Industry meets Academia, 2021 | 1 | 2021 |
Prof. Matthew P. JuniperProfessor of Thermofluids Dynamics, University of Cambridge在 cam.ac.uk 的电子邮件经过验证
