Andreas Lintermann

Orcid: 0000-0003-3321-6599

According to our database1, Andreas Lintermann authored at least 21 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

On csauthors.net:

Bibliography

2024
Distributed hybrid quantum-classical performance prediction for hyperparameter optimization.
Quantum Mach. Intell., December, 2024

On the choice of physical constraints in artificial neural networks for predicting flow fields.
Future Gener. Comput. Syst., 2024

Refining computer tomography data with super-resolution networks to increase the accuracy of respiratory flow simulations.
Future Gener. Comput. Syst., 2024

Robustness evaluation of large-scale machine learning-based reduced order models for reproducing flow fields.
Future Gener. Comput. Syst., 2024

Automated surgery planning for an obstructed nose by combining computational fluid dynamics with reinforcement learning.
Comput. Biol. Medicine, 2024

2023
Large scale performance analysis of distributed deep learning frameworks for convolutional neural networks.
J. Big Data, December, 2023

Short Paper: Accelerating Hyperparameter Optimization Algorithms with Mixed Precision.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Enabling Hyperparameter-Tuning of AI Models for Healthcare using the CoE RAISE Unique AI Framework for HPC.
Proceedings of the 46th MIPRO ICT and Electronics Convention, 2023

Optimal Resource Allocation for Early Stopping-based Neural Architecture Search Methods.
Proceedings of the International Conference on Automated Machine Learning, 2023

2022
An effective simulation- and measurement-based workflow for enhanced diagnostics in rhinology.
Medical Biol. Eng. Comput., 2022

A machine-learning-based method for automatizing lattice-Boltzmann simulations of respiratory flows.
Appl. Intell., 2022

Practice and Experience using High Performance Computing and Quantum Computing to Speed-up Data Science Methods in Scientific Applications.
Proceedings of the 45th Jubilee International Convention on Information, 2022

Accelerating Hyperparameter Tuning of a Deep Learning Model for Remote Sensing Image Classification.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022

2021
Effects of the Nasal Cavity Complexity on the Pharyngeal Airway Fluid Mechanics: A Computational Study.
J. Digit. Imaging, 2021

Machine-Learning-Based Control of Perturbed and Heated Channel Flows.
Proceedings of the High Performance Computing - ISC High Performance Digital 2021 International Workshops, Frankfurt am Main, Germany, June 24, 2021

Practice and Experience in using Parallel and Scalable Machine Learning with Heterogenous Modular Supercomputing Architectures.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium Workshops, 2021

2020
Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning.
Proceedings of the High Performance Computing, 2020

2019
Performance of ODROID-MC1 for scientific flow problems.
Future Gener. Comput. Syst., 2019

2018
Enabling Interactive Supercomputing at JSC Lessons Learned.
Proceedings of the High Performance Computing, 2018

2016
The Direct-Hybrid Method for Computational Aeroacoustics on HPC Systems.
Proceedings of the High-Performance Scientific Computing, 2016

2013
Fluid mechanics based classification of the respiratory efficiency of several nasal cavities.
Comput. Biol. Medicine, 2013


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