Matthias Ihme

Publication Activity (10 Years)

Years Active: 2008-2024
Publications (10 Years): 26

Top Topics

Linear Interpolation

Machine Learning

Processing Units

Top Venues

J. Comput. Phys.

Comput. Phys. Commun.

Publications

Nguyen Ly, Matthias Ihme
A regularized-interface method as a unified formulation for simulations of high-pressure multiphase flows. J. Comput. Phys. 518 (2024)
Niccolò Tonicello, Matthias Ihme
A high-order diffused-interface approach for two-phase compressible flow simulations using a discontinuous Galerkin framework. J. Comput. Phys. 508 (2024)
Andre Nicolle, Sili Deng, Matthias Ihme, Nursulu Kuzhagaliyeva, Emad Al Ibrahim, Aamir Farooq
Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview. J. Chem. Inf. Model. 64 (3) (2024)
Wai Tong Chung, Bassem Akoush, Pushan Sharma, Alex Tamkin, Ki Sung Jung, Jacqueline Chen, Jack Guo, Davy Brouzet, Mohsen Talei, Bruno Savard, Alexei Y. Poludnenko, Matthias Ihme
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. NeurIPS (2023)
Wai Tong Chung, Bassem Akoush, Pushan Sharma, Alex Tamkin, Ki Sung Jung, Jacqueline H. Chen, Jack Guo, Davy Brouzet, Mohsen Talei, Bruno Savard, Alexei Y. Poludnenko, Matthias Ihme
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data. CoRR (2023)
Sheide Chammas, Qing Wang, Tapio Schneider, Matthias Ihme, Yi-Fan Chen, John R. Anderson
Accelerating large-eddy simulations of clouds with Tensor Processing Units. CoRR (2023)
Eric J. Ching, Brett Bornhoft, Ali Lasemi, Matthias Ihme
Quail: A lightweight open-source discontinuous Galerkin code in Python for teaching and prototyping. SoftwareX 17 (2022)
John Burge, Matthew R. Bonanni, R. Lily Hu, Matthias Ihme
Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior. CoRR (2022)
Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar, Matthias Ihme, Yi-Fan Chen
Next Day Wildfire Spread: A Machine Learning Dataset to Predict Wildfire Spreading From Remote-Sensing Data. IEEE Trans. Geosci. Remote. Sens. 60 (2022)
Emeric Boigné, Dilworth Y. Parkinson, Matthias Ihme
Towards Data-Informed Motion Artifact Reduction in Quantitative CT Using Piecewise Linear Interpolation. IEEE Trans. Computational Imaging 8 (2022)
Wai Tong Chung, Ki Sung Jung, Jacqueline H. Chen, Matthias Ihme
The Bearable Lightness of Big Data: Towards Massive Public Datasets in Scientific Machine Learning. CoRR (2022)
Qing Wang, Matthias Ihme, Yi-Fan Chen, John R. Anderson
A TensorFlow simulation framework for scientific computing of fluid flows on tensor processing units. Comput. Phys. Commun. 274 (2022)
Wai Tong Chung, Aashwin Ananda Mishra, Nikolaos Perakis, Matthias Ihme
Accelerating High-fidelity Combustion Simulations with Classification Algorithms. AAAI Spring Symposium: MLPS (2021)
Eric J. Ching, Matthias Ihme
Efficient projection kernels for discontinuous Galerkin simulations of disperse multiphase flows on arbitrary curved elements. J. Comput. Phys. 435 (2021)
Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar, Matthias Ihme, Yi-Fan Chen
Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data. CoRR (2021)
Qing Wang, Matthias Ihme, Yi-Fan Chen, John R. Anderson
A TensorFlow Simulation Framework for Scientific Computing of Fluid Flows on Tensor Processing Units. CoRR (2021)
Eric J. Ching, Matthias Ihme
Development of a particle collision algorithm for discontinuous Galerkin simulations of compressible multiphase flows. J. Comput. Phys. 436 (2021)
Wai Tong Chung, Aashwin Ananda Mishra, Matthias Ihme
Interpretable Data-driven Methods for Subgrid-scale Closure in LES for Transcritical LOX/GCH4 Combustion. CoRR (2021)
Fantine Huot, R. Lily Hu, Matthias Ihme, Qing Wang, John Burge, Tianjian Lu, Jason Hickey, Yi-Fan Chen, John R. Anderson
Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data. CoRR (2020)
Wai Tong Chung, Aashwin Ananda Mishra, Nikolaos Perakis, Matthias Ihme
Data-assisted combustion simulations with dynamic submodel assignment using random forests. CoRR (2020)
Eric J. Ching, Steven R. Brill, Michael Barnhardt, Matthias Ihme
A two-way coupled Euler-Lagrange method for simulating multiphase flows with discontinuous Galerkin schemes on arbitrary curved elements. J. Comput. Phys. 405 (2020)
John Burge, Matthew Bonanni, Matthias Ihme, R. Lily Hu
Convolutional LSTM Neural Networks for Modeling Wildland Fire Dynamics. CoRR (2020)
Eric J. Ching, Yu Lv, Peter A. Gnoffo, Michael Barnhardt, Matthias Ihme
Shock capturing for discontinuous Galerkin methods with application to predicting heat transfer in hypersonic flows. J. Comput. Phys. 376 (2019)
Hao Wu, Peter C. Ma, Matthias Ihme
Efficient time-stepping techniques for simulating turbulent reactive flows with stiff chemistry. Comput. Phys. Commun. 243 (2019)
Peter C. Ma, Yu Lv, Matthias Ihme
An entropy-stable hybrid scheme for simulations of transcritical real-fluid flows. J. Comput. Phys. 340 (2017)
Yu Lv, Yee Chee See, Matthias Ihme
An entropy-residual shock detector for solving conservation laws using high-order discontinuous Galerkin methods. J. Comput. Phys. 322 (2016)
Yu Lv, Matthias Ihme
Entropy-bounded discontinuous Galerkin scheme for Euler equations. J. Comput. Phys. 295 (2015)
Yu Lv, Matthias Ihme
Discontinuous Galerkin method for multicomponent chemically reacting flows and combustion. J. Comput. Phys. 270 (2014)
Matthias Ihme, Lee Shunn, Jian Zhang
Regularization of reaction progress variable for application to flamelet-based combustion models. J. Comput. Phys. 231 (23) (2012)
Matthias Ihme, Alison L. Marsden, Heinz Pitsch
Generation of Optimal Artificial Neural Networks Using a Pattern Search Algorithm: Application to Approximation of Chemical Systems. Neural Comput. 20 (2) (2008)