Ensembling geophysical models with Bayesian Neural Networks. - Ushnish Sengupta; Matt Amos; J. Scott Hosking; Carl Edward Rasmussen; Matthew P. Juniper; Paul J. Young (NeurIPS, 2020)

Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles. - Ushnish Sengupta; Maximilian L. Croci; Matthew P. Juniper (CoRR, 2020)

Early Detection of Thermoacoustic Instabilities in a Cryogenic Rocket Thrust Chamber using Combustion Noise Features and Machine Learning. - Günther Waxenegger-Wilfing; Ushnish Sengupta; Jan Martin; Wolfgang Armbruster; Justin Hardi; Matthew P. Juniper; Michael Oschwald (CoRR, 2020)

Data Assimilation Using Heteroscedastic Bayesian Neural Network Ensembles for Reduced-Order Flame Models. - Maximilian L. Croci; Ushnish Sengupta; Matthew P. Juniper (ICCS (5), 2021)

Online parameter inference for the simulation of a Bunsen flame using heteroscedastic Bayesian neural network ensembles. - Maximilian L. Croci; Ushnish Sengupta; Matthew P. Juniper (CoRR, 2021)

Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning. - Ushnish Sengupta; Günther Waxenegger-Wilfing; Jan Martin; Justin Hardi; Matthew P. Juniper (CoRR, 2021)

Simultaneous boundary shape estimation and velocity field de-noising in Magnetic Resonance Velocimetry using Physics-informed Neural Networks. - Ushnish Sengupta; Alexandros Kontogiannis; Matthew P. Juniper (CoRR, 2021)

Meeting Changing Customer Requirements in Food and Agriculture Through the Application of Blockchain Technology. - Ushnish Sengupta; Henry M. Kim (Frontiers Blockchain, 2021)

Physics-informed Deep Learning for Flow Modelling and Aerodynamic Optimization. - Yubiao Sun; Ushnish Sengupta; Matthew P. Juniper (SSCI, 2022)

Generative Diffusion Models for Radio Wireless Channel Modelling and Sampling. - Ushnish Sengupta; Chinkuo Jao; Alberto Bernacchia; Sattar Vakili; Da-shan Shiu (GLOBECOM, 2023)

Score Normalization for a Faster Diffusion Exponential Integrator Sampler. - Guoxuan Xia; Duolikun Danier; Ayan Das 005; Stathi Fotiadis; Farhang Nabiei; Ushnish Sengupta; Alberto Bernacchia (CoRR, 2023)

A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms. - Gavin Abercrombie; Djalel Benbouzid; Paolo Giudici; Delaram Golpayegani; Julio Hernandez; Pierre Noro; Harshvardhan J. Pandit; Eva Paraschou; Charlie Pownall; Jyoti Prajapati; Mark A. Sayre; Ushnish Sengupta; et al. (CoRR, 2024)