Bernhard C. Geiger

1.2k total citations
75 papers, 580 citations indexed

About

Bernhard C. Geiger is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Bernhard C. Geiger has authored 75 papers receiving a total of 580 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 15 papers in Electrical and Electronic Engineering and 10 papers in Computer Networks and Communications. Recurrent topics in Bernhard C. Geiger's work include Neural Networks and Applications (8 papers), Advanced Combustion Engine Technologies (6 papers) and GNSS positioning and interference (6 papers). Bernhard C. Geiger is often cited by papers focused on Neural Networks and Applications (8 papers), Advanced Combustion Engine Technologies (6 papers) and GNSS positioning and interference (6 papers). Bernhard C. Geiger collaborates with scholars based in Austria, Germany and United States. Bernhard C. Geiger's co-authors include Rana Ali Amjad, Roman Kern, Christian Vogel, Stefan Posch, Gernot Kubin, Marek Śmieja, Gerhard Pirker, Patrick Ofner, Gorazd Kandus and Erich Leitgeb and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Automatic Control.

In The Last Decade

Bernhard C. Geiger

68 papers receiving 555 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bernhard C. Geiger Austria 14 197 137 95 87 59 75 580
G.V. Puskorius United States 12 613 3.1× 135 1.0× 44 0.5× 68 0.8× 34 0.6× 34 940
P. Lavoie Canada 13 192 1.0× 127 0.9× 149 1.6× 58 0.7× 69 1.2× 34 530
Jairo Espinosa Colombia 18 231 1.2× 221 1.6× 23 0.2× 20 0.2× 62 1.1× 98 1.2k
Timothy Sands United States 19 110 0.6× 136 1.0× 528 5.6× 127 1.5× 52 0.9× 73 1.1k
Ying Hung United States 13 156 0.8× 95 0.7× 40 0.4× 58 0.7× 17 0.3× 37 818
M. B. Zarrop United Kingdom 15 139 0.7× 122 0.9× 33 0.3× 34 0.4× 54 0.9× 50 1.1k
Alessandro N. Vargas Brazil 17 173 0.9× 156 1.1× 124 1.3× 20 0.2× 156 2.6× 77 990
H.A. Spang United States 10 69 0.4× 70 0.5× 106 1.1× 39 0.4× 33 0.6× 28 648

Countries citing papers authored by Bernhard C. Geiger

Since Specialization
Citations

This map shows the geographic impact of Bernhard C. Geiger's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bernhard C. Geiger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernhard C. Geiger more than expected).

Fields of papers citing papers by Bernhard C. Geiger

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bernhard C. Geiger. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bernhard C. Geiger. The network helps show where Bernhard C. Geiger may publish in the future.

Co-authorship network of co-authors of Bernhard C. Geiger

This figure shows the co-authorship network connecting the top 25 collaborators of Bernhard C. Geiger. A scholar is included among the top collaborators of Bernhard C. Geiger based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bernhard C. Geiger. Bernhard C. Geiger is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Geiger, Bernhard C., et al.. (2025). Detecting abrupt changes in missing time series data. Information Sciences. 717. 122322–122322.
2.
Geiger, Bernhard C., et al.. (2024). What’s so complex about conversational speech? A comparison of HMM-based and transformer-based ASR architectures. Computer Speech & Language. 90. 101738–101738. 1 indexed citations
3.
Posch, Stefan, et al.. (2024). Approximating families of sharp solutions to Fisher's equation with physics-informed neural networks. Computer Physics Communications. 307. 109422–109422.
4.
Geiger, Bernhard C., et al.. (2024). Robust Bayesian target vector optimization for multi-stage manufacturing processes. Computational Materials Science. 244. 113175–113175. 1 indexed citations
5.
Geiger, Bernhard C., et al.. (2023). Robust Bayesian target value optimization. Computers & Industrial Engineering. 180. 109279–109279. 8 indexed citations
6.
Geiger, Bernhard C., et al.. (2023). Reconsidering Read and Spontaneous Speech: Causal Perspectives on the Generation of Training Data for Automatic Speech Recognition. Information. 14(2). 137–137. 7 indexed citations
7.
Pirker, Gerhard, et al.. (2022). Estimation of Combustion Parameters from Engine Vibrations Based on Discrete Wavelet Transform and Gradient Boosting. Sensors. 22(11). 4235–4235. 13 indexed citations
8.
Geiger, Bernhard C., et al.. (2022). Gaussian Process Surrogates for Modeling Uncertainties in a Use Case of Forging Superalloys. Applied Sciences. 12(3). 1089–1089. 12 indexed citations
9.
Posch, Stefan, et al.. (2022). Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1-D Convolutional Neural Network Approach. IEEE/ASME Transactions on Mechatronics. 27(5). 4101–4111. 13 indexed citations
10.
Lovrić, Mario, Simonas Kecorius, Mark Kröll, et al.. (2022). Machine Learning and Meteorological Normalization for Assessment of Particulate Matter Changes during the COVID-19 Lockdown in Zagreb, Croatia. International Journal of Environmental Research and Public Health. 19(11). 6937–6937. 16 indexed citations
11.
Posch, Stefan, et al.. (2022). In-cylinder pressure reconstruction from engine block vibrations via a branched convolutional neural network. Mechanical Systems and Signal Processing. 183. 109640–109640. 9 indexed citations
12.
Pirker, Gerhard, et al.. (2021). Detection of Knocking Combustion Using the Continuous Wavelet Transformation and a Convolutional Neural Network. Energies. 14(2). 439–439. 21 indexed citations
13.
Geiger, Bernhard C.. (2021). On Information Plane Analyses of Neural Network Classifiers—A Review. IEEE Transactions on Neural Networks and Learning Systems. 33(12). 7039–7051. 5 indexed citations
14.
Geiger, Bernhard C. & Ian Fischer. (2020). A Comparison of Variational Bounds for the Information Bottleneck Functional. Entropy. 22(11). 1229–1229. 2 indexed citations
15.
Amjad, Rana Ali & Bernhard C. Geiger. (2019). Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(9). 2225–2239. 104 indexed citations
16.
Geiger, Bernhard C., et al.. (2019). Feature Extraction From Analog Wafermaps: A Comparison of Classical Image Processing and a Deep Generative Model. IEEE Transactions on Semiconductor Manufacturing. 32(2). 190–198. 17 indexed citations
17.
Amjad, Rana Ali, et al.. (2019). A Generalized Framework For Kullback–Leibler Markov Aggregation. IEEE Transactions on Automatic Control. 65(7). 3068–3075. 5 indexed citations
18.
Geiger, Bernhard C.. (2018). The Fractality of Polar and Reed–Muller Codes. Entropy. 20(1). 70–70. 3 indexed citations
19.
Bidokhti, Shirin Saeedi, et al.. (2017). A Rate-Distortion Approach to Caching. IEEE Transactions on Information Theory. 64(3). 1957–1976. 14 indexed citations
20.
Geiger, Bernhard C., et al.. (2012). Lumpings of Markov chains and entropy rate loss. arXiv (Cornell University). 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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