Comparison of Wireless Optical Communication Availability Data and Traffic Data. - Farukh Nadeem; Bernhard C. Geiger; Max Henkel; Erich Leitgeb; Muhammad Saleem Awan; Steve Hranilovic; Michael Gebhart; Gorazd Kandus (VTC Spring, 2009)

Implementation and analysis of load balancing switch over for hybrid wireless network. - Farukh Nadeem; Max Henkel; Bernhard C. Geiger; Erich Leitgeb; Muhammad Saleem Awan; Gorazd Kandus (WCNC, 2009)

Switch over implementation and analysis for hybrid wireless network of optical wireless and GHz links. - Farukh Nadeem; Bernhard C. Geiger; Max Henkel; Erich Leitgeb; Markus Löschnigg; Muhammad Saleem Awan; Abolfazl Chaman Motlagh; Gorazd Kandus (WTS, 2009)

On the detection probability of parallel code phase search algorithms in GPS receivers. - Bernhard C. Geiger; Michael Soudan; Christian Vogel 001 (PIMRC, 2010)

Information loss in static nonlinearities. - Bernhard C. Geiger; Christian Feldbauer; Gernot Kubin (ISWCS, 2011)

Some results on the information loss in dynamical systems. - Bernhard C. Geiger; Gernot Kubin (ISWCS, 2011)

Influence of Doppler Bin Width on GNSS Detection Probabilities - Bernhard C. Geiger; Christian Vogel 001 (CoRR, 2011)

On the Information Loss in Memoryless Systems: The Multivariate Case - Bernhard C. Geiger; Gernot Kubin (CoRR, 2011)

Comparison of link selection algorithms for free space optics/radio frequency hybrid network. - Farukh Nadeem; Bernhard C. Geiger; Erich Leitgeb; Sajid Sheikh Muhammad; Markus Löschnigg; Gorazd Kandus (IET Commun., 2011)

Capacity and capacity-achieving input distribution of the energy detector. - Erik Leitinger; Bernhard C. Geiger; Klaus Witrisal (ICUWB, 2012)

Relative information loss in the PCA. - Bernhard C. Geiger; Gernot Kubin (ITW, 2012)

Relative Information Loss - An Introduction - Bernhard C. Geiger; Gernot Kubin (CoRR, 2012)

Signal Enhancement as Minimization of Relevant Information Loss - Bernhard C. Geiger; Gernot Kubin (CoRR, 2012)

Lumped Markov chains and entropy rate - Bernhard C. Geiger; Christoph Temmel (CoRR, 2012)

Comparison Between Ratio Detection and Threshold Comparison for GNSS Acquisition. - Bernhard C. Geiger; Christian Vogel 001; Michael Soudan (IEEE Trans. Aerosp. Electron. Syst., 2012)

Double pitch marks in diplophonic voice. - Philipp Aichinger; Berit Schneider-Stickler; Wolfgang Bigenzahn; Anna Katharina Fuchs; Bernhard C. Geiger; Martin Hagmüller; Gernot Kubin (ICASSP, 2013)

Information-preserving Markov aggregation. - Bernhard C. Geiger; Christoph Temmel (ITW, 2013)

Greedy Part-Wise Learning of Sum-Product Networks. - Robert Peharz; Bernhard C. Geiger; Franz Pernkopf (ECML/PKDD (2), 2013)

Optimal M-Type Quantizations of Distributions. - Georg Böcherer; Bernhard C. Geiger (CoRR, 2013)

Information Loss and Anti-Aliasing Filters in Multirate Systems. - Bernhard C. Geiger; Gernot Kubin (CoRR, 2013)

Towards an information-theoretic system theory - Bernhard C. Geiger; Gernot Kubin (CoRR, 2013)

On the Rate of Information Loss in Memoryless Systems - Bernhard C. Geiger; Gernot Kubin (CoRR, 2013)

Influence of Doppler Bin Width on GPS Acquisition Probabilities. - Bernhard C. Geiger; Christian Vogel 001 (IEEE Trans. Aerosp. Electron. Syst., 2013)

A Matlab-based magnitude response game for DSP education. - Peter Casapicola; Markus Polzl; Bernhard C. Geiger (ICASSP, 2014)

Information-maximizing prefilters for quantization. - Bernhard C. Geiger; Gernot Kubin (ICASSP, 2014)

Lumpings of Markov Chains, Entropy Rate Preservation, and Higher-Order Lumpability. - Bernhard C. Geiger; Christoph Temmel (J. Appl. Probab., 2014)

The Muculants - a Higher-Order Statistical Approach. - Christian Knoll 002; Bernhard C. Geiger; Gernot Kubin (CoRR, 2015)

Optimal Kullback-Leibler Aggregation via Information Bottleneck. - Bernhard C. Geiger; Tatjana Petrov; Gernot Kubin; Heinz Koeppl (IEEE Trans. Autom. Control., 2015)

Graph-based lossless Markov lumpings. - Bernhard C. Geiger; Christoph Hofer-Temmel (ISIT, 2016)

Hard Clusters Maximize Mutual Information. - Bernhard C. Geiger; Rana Ali Amjad (CoRR, 2016)

Higher-Order Kullback-Leibler Aggregation of Markov Chains. - Bernhard C. Geiger; Yuchen Wu (CoRR, 2016)

Greedy Algorithms for Optimal Distribution Approximation. - Bernhard C. Geiger; Georg Böcherer (Entropy, 2016)

Information-Theoretic Analysis of Memoryless Deterministic Systems. - Bernhard C. Geiger; Gernot Kubin (Entropy, 2016)

The Magnitude Response Learning Tool for DSP Education: A Case Study. - Florian Kulmer; Christian Gun Wurzer; Bernhard C. Geiger (IEEE Trans. Educ., 2016)

Optimal Quantization for Distribution Synthesis. - Georg Bocherer; Bernhard C. Geiger (IEEE Trans. Inf. Theory, 2016)

Secret-key binding to physical identifiers with reliability guarantees. - Onur Günlü; Anes Belkacem; Bernhard C. Geiger (ICC, 2017)

On the information dimension rate of stochastic processes. - Bernhard C. Geiger; Tobias Koch 001 (ISIT, 2017)

Divergence scaling of fixed-length, binary-output, one-to-one distribution matching. - Patrick Schulte; Bernhard C. Geiger (ISIT, 2017)

On the Information Dimension of Multivariate Gaussian Processes. - Bernhard C. Geiger; Tobias Koch 001 (CoRR, 2017)

Semi-supervised cross-entropy clustering with information bottleneck constraint. - Marek Smieja; Bernhard C. Geiger (Inf. Sci., 2017)

How (Not) To Train Your Neural Network Using the Information Bottleneck Principle. - Rana Ali Amjad; Bernhard C. Geiger (CoRR, 2018)

Understanding Individual Neuron Importance Using Information Theory. - Kairen Liu; Rana Ali Amjad; Bernhard C. Geiger (CoRR, 2018)

A Short Note on the Jensen-Shannon Divergence between Simple Mixture Distributions. - Bernhard C. Geiger (CoRR, 2018)

The Fractality of Polar and Reed-Muller Codes. - Bernhard C. Geiger (Entropy, 2018)

A Rate-Distortion Approach to Caching. - Roy Timo; Shirin Saeedi Bidokhti; Michèle A. Wigger; Bernhard C. Geiger (IEEE Trans. Inf. Theory, 2018)

Class-Conditional Compression and Disentanglement: Bridging the Gap between Neural Networks and Naive Bayes Classifiers. - Rana Ali Amjad; Bernhard C. Geiger (CoRR, 2019)

SeGMA: Semi-Supervised Gaussian Mixture Auto-Encoder. - Marek Smieja; Maciej Wolczyk; Jacek Tabor; Bernhard C. Geiger (CoRR, 2019)

On the Information Dimension of Stochastic Processes. - Bernhard C. Geiger; Tobias Koch 001 (IEEE Trans. Inf. Theory, 2019)

Co-Clustering via Information-Theoretic Markov Aggregation. - Clemens Blöchl; Rana Ali Amjad; Bernhard C. Geiger (IEEE Trans. Knowl. Data Eng., 2019)

Das Theater mit dem Theater: Thementransfer in den Spectators. - Alexandra Fuchs; Bernhard C. Geiger; Elisabeth Hobisch; Philipp Koncar; Jacqueline More; Sanja Saric; Martina Scholger (DHd, 2020)

Behind the Scenes of the Spectators: Uncovering Anonymous Authors in Periodicals of the Enlightenment. - Elisabeth Hobisch; Martina Scholger; Alexandra Fuchs; Bernhard C. Geiger; Philipp Koncar; Sanja Saric (DH, 2020)

"To be or not to be central" - On the Stability of Network Centrality Measures in Shakespeare's "Hamlet". - Anastasia Klimashevskaia; Bernhard C. Geiger; Martin Hagmüller; Denis Helic; Frank Fischer 005 (DH, 2020)

Towards Accurate Simulation of Global Challenges on Data Centers Infrastructures via Coupling of Models and Data Sources. - Sergiy Gogolenko; Derek Groen; Diana Suleimenova; Imran Mahmood; Marcin Lawenda; Francisco Javier Nieto de Santos; John Hanley; Milana Vuckovic; Mark Kröll; Bernhard C. Geiger; Robert Elsässer; Dennis Hoppe (ICCS (6), 2020)

On Functions of Markov Random Fields. - Bernhard C. Geiger; Ali Al-Bashabsheh (ITW, 2020)

A generative semi-supervised classifier for datasets with unknown classes. - Stefan Schrunner; Bernhard C. Geiger; Anja Zernig; Roman Kern (SAC, 2020)

Text sentiment in the Age of Enlightenment: an analysis of spectator periodicals. - Philipp Koncar; Alexandra Fuchs; Elisabeth Hobisch; Bernhard C. Geiger; Martina Scholger; Denis Helic (Appl. Netw. Sci., 2020)

A Formally Robust Time Series Distance Metric. - Maximilian Toller; Bernhard C. Geiger; Roman Kern (CoRR, 2020)

A Comparison of Variational Bounds for the Information Bottleneck Functional. - Bernhard C. Geiger; Ian S. Fischer (Entropy, 2020)

Information Bottleneck: Theory and Applications in Deep Learning. - Bernhard C. Geiger; Gernot Kubin (Entropy, 2020)

Learning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle. - Rana Ali Amjad; Bernhard C. Geiger (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

A Generalized Framework For Kullback-Leibler Markov Aggregation. - Rana Ali Amjad; Clemens Blöchl; Bernhard C. Geiger (IEEE Trans. Autom. Control., 2020)

Importance of feature engineering and database selection in a machine learning model: A case study on carbon crystal structures. - Franz M. Rohrhofer; Santanu Saha; Simone Di Cataldo; Bernhard C. Geiger; Wolfgang von der Linden; Lilia Boeri (CoRR, 2021)

On the Pareto Front of Physics-Informed Neural Networks. - Franz M. Rohrhofer; Stefan Posch; Bernhard C. Geiger (CoRR, 2021)

Semi-Supervised Clustering via Markov Chain Aggregation. - Sophie Steger; Bernhard C. Geiger; Marek Smieja (CoRR, 2021)

A Geometric Perspective on Information Plane Analysis. - Mina Basirat; Bernhard C. Geiger; Peter M. Roth (Entropy, 2021)

SeGMA: Semi-Supervised Gaussian Mixture Autoencoder. - Marek Smieja; Maciej Wolczyk; Jacek Tabor; Bernhard C. Geiger (IEEE Trans. Neural Networks Learn. Syst., 2021)

Camp Location Selection in Humanitarian Logistics: A Multiobjective Simulation Optimization Approach. - Yani Xue; Miqing Li; Hamid Arabnejad; Diana Suleimenova; Alireza Jahani; Bernhard C. Geiger; Zidong Wang 001; Xiaohui Liu 001; Derek Groen (ICCS (3), 2022)

Compressed Hierarchical Representations for Multi-Task Learning and Task Clustering. - João Machado de Freitas; Sebastian Berg; Bernhard C. Geiger; Manfred Mücke (IJCNN, 2022)

Semi-supervised clustering via information-theoretic markov chain aggregation. - Sophie Steger; Bernhard C. Geiger; Marek Smieja (SAC, 2022)

Generating Simple Directed Social Network Graphs for Information Spreading. - Christoph Schweimer; Christine Gfrerer; Florian Lugstein; David Pape; Jan A. Velimsky; Robert Elsässer; Bernhard C. Geiger (WWW, 2022)

Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1D Convolutional Neural Network Approach. - Andreas B. Ofner; Achilles Kefalas; Stefan Posch; Bernhard C. Geiger (CoRR, 2022)

Understanding the Difficulty of Training Physics-Informed Neural Networks on Dynamical Systems. - Franz M. Rohrhofer; Stefan Posch; Clemens Gößnitzer; Bernhard C. Geiger (CoRR, 2022)

Information-Theoretic Reduction of Markov Chains. - Bernhard C. Geiger (CoRR, 2022)

FUNCK: Information Funnels and Bottlenecks for Invariant Representation Learning. - João Machado de Freitas; Bernhard C. Geiger (CoRR, 2022)

Synwalk: community detection via random walk modelling. - Christian Toth; Denis Helic; Bernhard C. Geiger (Data Min. Knowl. Discov., 2022)

Estimation of Combustion Parameters from Engine Vibrations Based on Discrete Wavelet Transform and Gradient Boosting. - Achilles Kefalas; Andreas B. Ofner; Gerhard Pirker; Stefan Posch; Bernhard C. Geiger; Andreas Wimmer (Sensors, 2022)

Understanding Neural Networks and Individual Neuron Importance via Information-Ordered Cumulative Ablation. - Rana Ali Amjad; Kairen Liu; Bernhard C. Geiger (IEEE Trans. Neural Networks Learn. Syst., 2022)

On Information Plane Analyses of Neural Network Classifiers - A Review. - Bernhard C. Geiger (IEEE Trans. Neural Networks Learn. Syst., 2022)

Markov Aggregation for Speeding Up Agent-Based Movement Simulations. - Bernhard C. Geiger; Alireza Jahani; Hussain Hussain; Derek Groen (AAMAS, 2023)

Information Plane Analysis for Dropout Neural Networks. - Linara Adilova; Bernhard C. Geiger; Asja Fischer (ICLR, 2023)

Exploring Graph Theory Methods For the Analysis of Pronunciation Variation in Spontaneous Speech. - Bernhard C. Geiger; Barbara Schuppler (INTERSPEECH, 2023)

Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks. - Franz M. Rohrhofer; Stefan Posch; Clemens Gößnitzer; Bernhard C. Geiger (IEEE Access, 2023)

A conceptual model for leaving the data-centric approach in machine learning. - Sebastian Scher; Bernhard C. Geiger; Simone Kopeinik; Andreas Trügler; Dominik Kowald (CoRR, 2023)

Finding the Optimum Design of Large Gas Engines Prechambers Using CFD and Bayesian Optimization. - Stefan Posch; Clemens Gößnitzer; Franz M. Rohrhofer; Bernhard C. Geiger; Andreas Wimmer (CoRR, 2023)

Bringing Chemistry to Scale: Loss Weight Adjustment for Multivariate Regression in Deep Learning of Thermochemical Processes. - Franz M. Rohrhofer; Stefan Posch; Clemens Gößnitzer; José M. García-Oliver; Bernhard C. Geiger (CoRR, 2023)

Cluster Purging: Efficient Outlier Detection Based on Rate-Distortion Theory. - Maximilian Toller; Bernhard C. Geiger; Roman Kern (IEEE Trans. Knowl. Data Eng., 2023)

On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks. - Franz M. Rohrhofer; Stefan Posch; Clemens Gößnitzer; Bernhard C. Geiger (Trans. Mach. Learn. Res., 2023)

Reconsidering Read and Spontaneous Speech: Causal Perspectives on the Generation of Training Data for Automatic Speech Recognition. - Philipp Gabler; Bernhard C. Geiger; Barbara Schuppler; Roman Kern (Inf., 2023)

Robust Bayesian target value optimization. - Johannes G. Hoffer; Sascha Ranftl; Bernhard C. Geiger (Comput. Ind. Eng., 2023)

Constraining Anomaly Detection with Anomaly-Free Regions. - Maximilian Toller; Hussain Hussain; Roman Kern; Bernhard C. Geiger (ICKG, 2024)

Towards Improving ASR Outputs of Spontaneous Speech with LLMs. - Karner Manuel; Julian Linke; Mark Kröll; Barbara Schuppler; Bernhard C. Geiger (KONVENS, 2024)

Value Identification in Multistakeholder Recommender Systems for Humanities and Historical Research: The Case of the Digital Archive Monasterium.net. - Florian Atzenhofer-Baumgartner; Bernhard C. Geiger; Georg Vogeler; Dominik Kowald (NORMalize@RecSys, 2024)

Activation Bottleneck: Sigmoidal Neural Networks Cannot Forecast a Straight Line. - Maximilian Toller; Hussain Hussain; Bernhard C. Geiger (CoRR, 2024)

Challenges in Implementing a Recommender System for Historical Research in the Humanities. - Florian Atzenhofer-Baumgartner; Bernhard C. Geiger; Christoph Trattner; Georg Vogeler; Dominik Kowald (CoRR, 2024)

Approximating families of sharp solutions to Fisher's equation with physics-informed neural networks. - Franz M. Rohrhofer; Stefan Posch; Clemens Gößnitzer; Bernhard C. Geiger (Comput. Phys. Commun., 2025)

What's so complex about conversational speech? A comparison of HMM-based and transformer-based ASR architectures. - Julian Linke; Bernhard C. Geiger; Gernot Kubin; Barbara Schuppler (Comput. Speech Lang., 2025)

Detecting abrupt changes in missing time series data. - Maximilian B. Toller; Bernhard C. Geiger; Roman Kern (Inf. Sci., 2025)

On the Role of Priors in Bayesian Causal Learning. - Bernhard C. Geiger; Roman Kern (IEEE Trans. Artif. Intell., 2025)

B-PL-PINN: Stabilizing PINN Training with Bayesian Pseudo Labeling. - Kevin Innerebner; Franz M. Rohrhofer; Bernhard C. Geiger (CoRR, 2025)