Matthew P. Juniper

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 17

Top Topics

Stability Analysis

Neural Network Ensembles

Parameter Learning

Top Venues

J. Comput. Phys.

IEEE Trans. Image Process.

Publications

Alexandros Kontogiannis, Scott V. Elgersma, Andrew J. Sederman, Matthew P. Juniper
Bayesian inverse Navier-Stokes problems: joint flow field reconstruction and parameter learning. CoRR (2024)
Alexandros Kontogiannis, Matthew P. Juniper
Physics-Informed Compressed Sensing for PC-MRI: An Inverse Navier-Stokes Problem. IEEE Trans. Image Process. 32 (2023)
Yubiao Sun, Ushnish Sengupta, Matthew P. Juniper
Physics-informed Deep Learning for Flow Modelling and Aerodynamic Optimization. SSCI (2022)
Alexandros Kontogiannis, Matthew P. Juniper
Physics-informed compressed sensing for PC-MRI: an inverse Navier-Stokes problem. CoRR (2022)
Ushnish Sengupta, Günther Waxenegger-Wilfing, Jan Martin, Justin Hardi, Matthew P. Juniper
Forecasting Thermoacoustic Instabilities in Liquid Propellant Rocket Engines Using Multimodal Bayesian Deep Learning. CoRR (2021)
Ushnish Sengupta, Alexandros Kontogiannis, Matthew P. Juniper
Simultaneous boundary shape estimation and velocity field de-noising in Magnetic Resonance Velocimetry using Physics-informed Neural Networks. CoRR (2021)
Maximilian L. Croci, Ushnish Sengupta, Matthew P. Juniper
Online parameter inference for the simulation of a Bunsen flame using heteroscedastic Bayesian neural network ensembles. CoRR (2021)
Maximilian L. Croci, Ushnish Sengupta, Matthew P. Juniper
Data Assimilation Using Heteroscedastic Bayesian Neural Network Ensembles for Reduced-Order Flame Models. ICCS (5) (2021)
Ushnish Sengupta, Maximilian L. Croci, Matthew P. Juniper
Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles. CoRR (2020)
Günther Waxenegger-Wilfing, Ushnish Sengupta, Jan Martin, Wolfgang Armbruster, Justin Hardi, Matthew P. Juniper, Michael Oschwald
Early Detection of Thermoacoustic Instabilities in a Cryogenic Rocket Thrust Chamber using Combustion Noise Features and Machine Learning. CoRR (2020)
Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young
Ensembling geophysical models with Bayesian Neural Networks. NeurIPS (2020)
Ushnish Sengupta, Matt Amos, J. Scott Hosking, Carl Edward Rasmussen, Matthew P. Juniper, Paul J. Young
Ensembling geophysical models with Bayesian Neural Networks. CoRR (2020)
Hans Yu, Matthew P. Juniper, Luca Magri
Combined state and parameter estimation in level-set methods. J. Comput. Phys. 399 (2019)
Hans Yu, Matthew P. Juniper, Luca Magri
Combined State and Parameter Estimation in Level-Set Methods. CoRR (2019)
José G. Aguilar, Luca Magri, Matthew P. Juniper
Adjoint-based sensitivity analysis of low-order thermoacoustic networks using a wave-based approach. J. Comput. Phys. 341 (2017)
Luca Magri, Michael Bauerheim, Franck Nicoud, Matthew P. Juniper
Stability analysis of thermo-acoustic nonlinear eigenproblems in annular combustors. Part II. Uncertainty quantification. J. Comput. Phys. 325 (2016)
Luca Magri, Michael Bauerheim, Matthew P. Juniper
Stability analysis of thermo-acoustic nonlinear eigenproblems in annular combustors. Part I. Sensitivity. J. Comput. Phys. 325 (2016)
Iain Waugh, Simon Illingworth, Matthew P. Juniper
Matrix-free continuation of limit cycles for bifurcation analysis of large thermoacoustic systems. J. Comput. Phys. 240 (2013)
Gary J. Chandler, Matthew P. Juniper, Joseph W. Nichols, Peter J. Schmid
Adjoint algorithms for the Navier-Stokes equations in the low Mach number limit. J. Comput. Phys. 231 (4) (2012)