Bernhard C. Geiger

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Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1D Convolutional Neural Network Approach pdf

Stefan Posch, Andreas B. Ofner, Achilles Kefalas, 2022, ArXiv.

Detection of Knocking Combustion Using the Continuous Wavelet Transformation and a Convolutional Neural Network

Andreas Wimmer, Gerhard Pirker, Stefan Posch, 2021, Energies.

A Route Pruning Algorithm for an Automated Geographic Location Graph Construction

Derek Groen, Imran Mahmood, Diana Suleimenova, 2021 .

Theory-inspired machine learning—towards a synergy between knowledge and data

Bernhard C. Geiger, M. Lovrić, Roman Kern, 2022, Welding in the World.

Generating Simple Directed Social Network Graphs for Information Spreading

Bernhard C. Geiger, Robert Elsässer, Christoph Schweimer, 2022, WWW.

Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia

Bernhard C. Geiger, M. Lovrić, I. Šimić, 2022, International journal of environmental research and public health.

Theory-inspired machine learning—towards a synergy between knowledge and data

Franz M. Rohrhofer, Bernhard C. Geiger, M. Lovrić, 2022, Welding in the World.

Big Data and Data Driven Modeling -- A New Dawn for Engine Operation and Development

Stefanie N. Lindstaedt, Stefanie Lindstaedt, Bernhard Geiger, 2019 .

Reconsidering Read and Spontaneous Speech: Causal Perspectives on the Generation of Training Data for Automatic Speech Recognition

Bernhard C. Geiger, Roman Kern, Barbara Schuppler, 2023, Inf..

Estimation of Combustion Parameters from Engine Vibrations Based on Discrete Wavelet Transform and Gradient Boosting

Bernhard C. Geiger, G. Pirker, A. Wimmer, 2022, Sensors.

A Comparison of Virtual Sensors for Combustion Parameter Prediction of Gas Engines Based on Knock Sensor Signals

Bernhard C. Geiger, G. Pirker, A. Wimmer, 2023, SAE Technical Paper Series.

In-cylinder pressure reconstruction from engine block vibrations via a branched convolutional neural network

Bernhard C. Geiger, G. Pirker, S. Posch, 2022, Mechanical Systems and Signal Processing.

Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1-D Convolutional Neural Network Approach

Bernhard C. Geiger, André Ofner, S. Posch, 2022, IEEE/ASME transactions on mechatronics.

On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks

Bernhard C. Geiger, F. Rohrhofer, S. Posch, 2022, Trans. Mach. Learn. Res..

Understanding the Difficulty of Training Physics-Informed Neural Networks on Dynamical Systems

Franz M. Rohrhofer, Bernhard C. Geiger, F. Rohrhofer, 2022, ArXiv.

Camp Location Selection in Humanitarian Logistics: A Multiobjective Simulation Optimization Approach

Bernhard C. Geiger, M. Li, D. Groen, 2022, International Conference on Conceptual Structures.

Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks

Franz M. Rohrhofer, Bernhard C. Geiger, S. Posch, 2023, IEEE Access.

Bringing Chemistry to Scale: Loss Weight Adjustment for Multivariate Regression in Deep Learning of Thermochemical Processes

Franz M. Rohrhofer, Bernhard C. Geiger, S. Posch, 2023, arXiv.org.

Finding the Optimum Design of Large Gas Engines Prechambers Using CFD and Bayesian Optimization

Franz M. Rohrhofer, Bernhard C. Geiger, A. Wimmer, 2023, ArXiv.

Generating Simple Directed Social Network Graphs for Information Spreading

Bernhard C. Geiger, Robert Elsässer, Christoph Schweimer, 2022, WWW.

Utilizing neural networks to supplant chemical kinetics tabulation through mass conservation and weighting of species depletion

Franz M. Rohrhofer, Bernhard C. Geiger, J. M. García-Oliver, 2024, Energy and AI.