Matthew P. Juniper

21 papers A* 1Journal 18Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Helmholtz-x : Parallelized adjoint open source solver for the thermoacoustic Helmholtz equation.
Eng. Comput.
Ekrem Ekici, Stefano Falco, Matthew P. Juniper
2024 J jnl
Bayesian inference of mean velocity fields and turbulence models from flow MRI.
CoRR
Alexandros Kontogiannis, Priya J. Nair, Michael Loecher, Daniel B. Ennis, Alison L. Marsden, Matthew P. Juniper
2024 J jnl
Bayesian inverse Navier-Stokes problems: joint flow field reconstruction and parameter learning.
CoRR
Alexandros Kontogiannis, Scott V. Elgersma, Andrew J. Sederman, Matthew P. Juniper
2023 J jnl
Physics-Informed Compressed Sensing for PC-MRI: An Inverse Navier-Stokes Problem.
IEEE Trans. Image Process.
Alexandros Kontogiannis, Matthew P. Juniper
2022 — conf
Physics-informed Deep Learning for Flow Modelling and Aerodynamic Optimization.
SSCI
Yubiao Sun, Ushnish Sengupta, Matthew P. Juniper
2022 J jnl
Physics-informed compressed sensing for PC-MRI: an inverse Navier-Stokes problem.
CoRR
Alexandros Kontogiannis, Matthew P. Juniper
2021 — conf
Data Assimilation Using Heteroscedastic Bayesian Neural Network Ensembles for Reduced-Order Flame Models.
ICCS (5)
Maximilian L. Croci, Ushnish Sengupta, Matthew P. Juniper
2021 J jnl
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning.
CoRR
Ushnish Sengupta, Günther Waxenegger-Wilfing, Jan Martin, Justin Hardi, Matthew P. Juniper
2021 J jnl
Online parameter inference for the simulation of a Bunsen flame using heteroscedastic Bayesian neural network ensembles.
CoRR
Maximilian L. Croci, Ushnish Sengupta, Matthew P. Juniper
2021 J jnl
Simultaneous boundary shape estimation and velocity field de-noising in Magnetic Resonance Velocimetry using Physics-informed Neural Networks.
CoRR
Ushnish Sengupta, Alexandros Kontogiannis, Matthew P. Juniper
2020 J jnl
Early Detection of Thermoacoustic Instabilities in a Cryogenic Rocket Thrust Chamber using Combustion Noise Features and Machine Learning.
CoRR
Günther Waxenegger-Wilfing, Ushnish Sengupta, Jan Martin, Wolfgang Armbruster, Justin Hardi, Matthew P. Juniper, Michael Oschwald
2020 A* conf
Ensembling geophysical models with Bayesian Neural Networks.
NeurIPS
Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young
2020 J jnl
Ensembling geophysical models with Bayesian Neural Networks.
CoRR
Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young
2020 J jnl
Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles.
CoRR
Ushnish Sengupta, Maximilian L. Croci, Matthew P. Juniper
2019 J jnl
Combined State and Parameter Estimation in Level-Set Methods.
CoRR
Hans Yu, Matthew P. Juniper, Luca Magri
2019 J jnl
Combined state and parameter estimation in level-set methods.
J. Comput. Phys.
Hans Yu, Matthew P. Juniper, Luca Magri
2017 J jnl
Adjoint-based sensitivity analysis of low-order thermoacoustic networks using a wave-based approach.
J. Comput. Phys.
José G. Aguilar, Luca Magri, Matthew P. Juniper
2016 J jnl
Stability analysis of thermo-acoustic nonlinear eigenproblems in annular combustors. Part I. Sensitivity.
J. Comput. Phys.
Luca Magri, Michael Bauerheim, Matthew P. Juniper
2016 J jnl
Stability analysis of thermo-acoustic nonlinear eigenproblems in annular combustors. Part II. Uncertainty quantification.
J. Comput. Phys.
Luca Magri, Michael Bauerheim, Franck Nicoud, Matthew P. Juniper
2013 J jnl
Matrix-free continuation of limit cycles for bifurcation analysis of large thermoacoustic systems.
J. Comput. Phys.
Iain Waugh, Simon Illingworth, Matthew P. Juniper
2012 J jnl
Adjoint algorithms for the Navier-Stokes equations in the low Mach number limit.
J. Comput. Phys.
Gary J. Chandler, Matthew P. Juniper, Joseph W. Nichols, Peter J. Schmid