Workshop for Doctoral students in Fuzzy-Based Systems. - Johann Gamper; Bernhard Moser 001 (FLAI, 1993)

On the redundancy of fuzzy partitions. - Erich-Peter Klement; Bernhard Moser 001 (Fuzzy Sets Syst., 1997)

Which triangular norms are convenient for fuzzy controllers?. - Bernhard Moser 001; Mirko Navara (EUSFLAT-ESTYLF Joint Conf., 1999)

Sugeno controllers with a bounded number of rules are nowhere dense. - Bernhard Moser 001 (Fuzzy Sets Syst., 1999)

Convex combinations in terms of triangular norms: A characterization of idempotent, bisymmetrical and self-dual compensatory operators. - Bernhard Moser 001; Elena Tsiporkova; Erich-Peter Klement (Fuzzy Sets Syst., 1999)

A relationship between equality relations and the T-redundancy of fuzzy partitions and its application to Sugeno controllers. - Bernhard Moser 001; Roman Winkler (Fuzzy Sets Syst., 2000)

Stability of interpolative fuzzy KH controllers. - Domonkos Tikk; István Joó; László T. Kóczy; Péter Várlaki; Bernhard Moser 001; Tamás D. Gedeon (Fuzzy Sets Syst., 2002)

Fuzzy controllers with conditionally firing rules. - Bernhard Moser 001; Mirko Navara (IEEE Trans. Fuzzy Syst., 2002)

Correspondences Between Fuzzy Equivalence Relations and Kernels: Theoretical Results and Potential Applications. - Bernhard Moser 001; Ulrich Bodenhofer (FUZZ-IEEE, 2006)

On the T. - Bernhard Moser 001 (Fuzzy Sets Syst., 2006)

On Representing and Generating Kernels by Fuzzy Equivalence Relations. - Bernhard Moser 001 (J. Mach. Learn. Res., 2006)

Denoising techniques for raw 3D data of TOF cameras based on clustering and wavelets. - Bernhard Moser 001; Frank Bauer; Peter Elbau; Bettina Heise; Holger Schöner (Three-Dimensional Image Capture and Applications, 2008)

On the Potential of Hermann Weyl's Discrepancy Norm for Texture Analysis. - Bernhard Moser 001; Peter Haslinger; Tomas Kazmar (CIMCA/IAWTIC/ISE, 2008)

A Clustering Based Denoising Technique for Range Images of Time of Flight Cameras. - Holger Schöner; Bernhard Moser 001; Adrian A. Dorrington; Andrew D. Payne; Michael J. Cree; Bettina Heise; Frank Bauer (CIMCA/IAWTIC/ISE, 2008)

On Preprocessing Multi-channel Sensor Data for Online Process Monitoring. - Holger Schöner; Bernhard Moser 001; Edwin Lughofer (CIMCA/IAWTIC/ISE, 2008)

Data-Driven and Knowledge-Based Modeling. - Erich-Peter Klement; Edwin Lughofer; Johannes Himmelbauer; Bernhard Moser 001 (Hagenberg Research, 2009)

Parallel, Distributed, and Grid Computing. - Wolfgang Schreiner; Károly Bósa; Andreas Langegger; Thomas Leitner; Bernhard Moser 001; Szilárd Páll; Volkmar Wieser; Wolfram Wöß (Hagenberg Research, 2009)

A Data-Mining Approach to 3D Realistic Render Setup Assistance. - Carlos González-Morcillo; Lorenzo Manuel López-López; José Jesús Castro Sanchez; Bernhard Moser 001 (IAAI, 2009)

On the compactness of admissible transformations of fuzzy partitions in terms of T-equivalence relations. - Bernhard Moser 001 (Fuzzy Sets Syst., 2009)

On autocorrelation based on Hermann Weyl's discrepancy norm for time series analysis. - Jean-Luc Bouchot; Johannes Himmelbauer; Bernhard Moser 001 (IJCNN, 2010)

GPU-Based Image Processing Use Cases: A High-Level Approach. - Volkmar Wieser; Clemens Grelck; Holger Schöner; Peter Haslinger; Károly Bósa; Bernhard Moser 001 (PARCO, 2011)

On a Non-monotonicity Effect of Similarity Measures. - Bernhard Moser 001; Gernot Stübl; Jean-Luc Bouchot (SIMBAD, 2011)

A Similarity Measure for Image and Volumetric Data Based on Hermann Weyl's Discrepancy. - Bernhard Moser 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2011)

Discrepancy Norm as Fitness Function for Defect Detection on Regularly Textured Surfaces. - Gernot Stübl; Jean-Luc Bouchot; Peter Haslinger; Bernhard Moser 001 (DAGM/OAGM Symposium, 2012)

Geometric Characterization of Weyl's Discrepancy Norm in Terms of Its n-Dimensional Unit Balls. - Bernhard Alois Moser (Discret. Comput. Geom., 2012)

Image processing for three-dimensional scans generated by time-of-flight range cameras. - Holger Schöner; Frank Bauer; Adrian A. Dorrington; Bettina Heise; Volkmar Wieser; Andrew D. Payne; Michael J. Cree; Bernhard Moser 001 (J. Electronic Imaging, 2012)

Combining high productivity and high performance in image processing using Single Assignment C on multi-core CPUs and many-core GPUs. - Volkmar Wieser; Clemens Grelck; Peter Haslinger; Jing Guo; Filip Korzeniowski; Robert Bernecky; Bernhard Moser 001; Sven-Bodo Scholz (J. Electronic Imaging, 2012)

Periodicity estimation of nearly regular textures based on discrepancy norm. - Gernot Stübl; Peter Haslinger; Volkmar Wieser; Josef Scharinger; Bernhard Moser 001 (Image Processing: Machine Vision Applications, 2013)

On the Relevance of Discrepancy Norm for Similarity-Based Clustering of Delta-Event Sequences. - Bernhard Moser 001; Florian Eibensteiner; Jürgen Kogler; Gernot Stübl (EUROCAST (1), 2013)

On Approximate Nearest Neighbour Field Algorithms in Template Matching for Surface Quality Inspection. - Gernot Stübl; Bernhard Moser 001; Josef Scharinger (EUROCAST (2), 2013)

The Range of a Simple Random Walk on Z: An Elementary Combinatorial Approach. - Bernhard Alois Moser (Electron. J. Comb., 2014)

On Stability of Distance Measures for Event Sequences Induced by Level-Crossing Sampling. - Bernhard Alois Moser; Thomas Natschläger (IEEE Trans. Signal Process., 2014)

Matching event sequences approach based on Weyl's discrepancy norm. - Bernhard Alois Moser (EBCCSP, 2015)

Stability of threshold-based sampling as metric problem. - Bernhard Alois Moser (EBCCSP, 2015)

Trifocal system for high-quality inter-camera mapping and virtual view synthesis. - Florian H. Seitner; Matej Nezveda; Margrit Gelautz; Georg Braun; Christian Kapeller; Werner Zellinger; Bernhard Moser 001 (IC3D, 2015)

On preserving metric properties of integrate-and-fire sampling. - Bernhard Alois Moser (EBCCSP, 2016)

Linear Optimization Approach for Depth Range Adaption of Stereoscopic Videos. - Werner Zellinger; Bernhard Moser 001; Ayadi Chouikhi; Florian H. Seitner; Matej Nezveda; Margrit Gelautz (SD&A, 2016)

Improving Visual Discomfort Prediction for Stereoscopic Images via Disparity-based Contrast. - Werner Zellinger; Bernhard Moser 001 (IQSP, 2016)

Estimating the signal reconstruction error from threshold-based sampling without knowing the original signal. - Bernhard Alois Moser (EBCCSP, 2017)

Similarity Recovery From Threshold-Based Sampling Under General Conditions. - Bernhard Alois Moser (IEEE Trans. Signal Process., 2017)

ALOHA: an architectural-aware framework for deep learning at the edge. - Paolo Meloni; Daniela Loi; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Bernhard Moser 001; Natalia Shepeleva; Francesco Conti 001; Luca Benini; Oscar Ripolles; David Solans; Maura Pintor; et al. (INTESA@ESWEEK, 2018)

Architecture-aware design and implementation of CNN algorithms for embedded inference: the ALOHA project. - Paolo Meloni; Daniela Loi; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Maura Pintor; Battista Biggio; Oscar Ripolles; David Solans; Francesco Conti 001; Luca Benini; Todor P. Stefanov; et al. (ICM, 2018)

Deep SNP: An End-to-end Deep Neural Network with Attention-based Localization for Break-point Detection in SNP Array Genomic data. - Hamid Eghbal-zadeh; Lukas Fischer 001; Niko Popitsch; Florian Kromp; Sabine Taschner-Mandl; Khaled Koutini; Teresa Gerber; Eva Bozsaky; Peter F. Ambros; Inge M. Ambros; Gerhard Widmer; Bernhard Alois Moser (CoRR, 2018)

Optimization and deployment of CNNs at the edge: the ALOHA experience. - Paolo Meloni; Daniela Loi; Paola Busia; Gianfranco Deriu; Andy D. Pimentel; Dolly Sapra; Todor P. Stefanov; Svetlana Minakova; Francesco Conti 001; Luca Benini; Maura Pintor; Battista Biggio; et al. (CF, 2019)

Deriving an Optimal Noise Adding Mechanism for Privacy-Preserving Machine Learning. - Mohit Kumar 001; Michael Rossbory; Bernhard Alois Moser; Bernhard Freudenthaler (DEXA Workshops, 2019)

Tradeoff Analysis of Discrepancy-Based Adaptive Thresholding Approach. - Michael Lunglmayr; Saeed Mian Qaisar; Bernhard Alois Moser (EBCCSP, 2019)

An Event-Driven Approach for Time-Domain Recognition of Spoken English Letters. - Saeed Mian Qaisar; S. Laskar; Michael Lunglmayr; Bernhard Alois Moser; R. Abdulbaqi; R. Banafia (EBCCSP, 2019)

Domain-Invariant Regression Under Beer-Lambert's Law. - Ramin Nikzad-Langerodi; Werner Zellinger; Susanne Saminger-Platz; Bernhard Moser 001 (ICMLA, 2019)

Robust unsupervised domain adaptation for neural networks via moment alignment. - Werner Zellinger; Bernhard Alois Moser; Thomas Grubinger; Edwin Lughofer; Thomas Natschläger; Susanne Saminger-Platz (Inf. Sci., 2019)

DeepSNP: An End-to-End Deep Neural Network with Attention-Based Localization for Breakpoint Detection in Single-Nucleotide Polymorphism Array Genomic Data. - Hamid Eghbal-Zadeh; Lukas Fischer 001; Niko Popitsch; Florian Kromp; Sabine Taschner-Mandl; Teresa Gerber; Eva Bozsaky; Peter F. Ambros; Inge M. Ambros; Gerhard Widmer; Bernhard Alois Moser (J. Comput. Biol., 2019)

On Quasi-Isometry of Threshold-Based Sampling. - Bernhard Alois Moser; Michael Lunglmayr (IEEE Trans. Signal Process., 2019)

Applying AI in Practice: Key Challenges and Lessons Learned. - Lukas Fischer 001; Lisa Ehrlinger; Verena Geist; Rudolf Ramler; Florian Sobieczky; Werner Zellinger; Bernhard Moser 001 (CD-MAKE, 2020)

Variational Optimization of Informational Privacy. - Mohit Kumar 001; David Brunner; Bernhard Alois Moser; Bernhard Freudenthaler (DEXA Workshops, 2020)

Beyond federated learning: On confidentiality-critical machine learning applications in industry. - Werner Zellinger; Volkmar Wieser; Mohit Kumar 001; David Brunner; Natalia Shepeleva; Rafa Gálvez; Josef Langer; Lukas Fischer 001; Bernhard Moser 001 (ISM, 2020)

Differentially Private Learning of Distributed Deep Models. - Mohit Kumar 001; Michael Rossbory; Bernhard Alois Moser; Bernhard Freudenthaler (UMAP (Adjunct Publication), 2020)

Learning Bounds for Moment-Based Domain Adaptation. - Werner Zellinger; Bernhard Alois Moser; Susanne Saminger-Platz (CoRR, 2020)

ReLU Code Space: A Basis for Rating Network Quality Besides Accuracy. - Natalia Shepeleva; Werner Zellinger; Michal Lewandowski; Bernhard Moser 001 (CoRR, 2020)

On Data Augmentation and Adversarial Risk: An Empirical Analysis. - Hamid Eghbal-zadeh; Khaled Koutini; Paul Primus; Verena Haunschmid; Michal Lewandowski; Werner Zellinger; Bernhard Alois Moser; Gerhard Widmer (CoRR, 2020)

Domain adaptation for regression under Beer-Lambert's law. - Ramin Nikzad-Langerodi; Werner Zellinger; Susanne Saminger-Platz; Bernhard Alois Moser (Knowl. Based Syst., 2020)

Membership-Mappings for Data Representation Learning: Measure Theoretic Conceptualization. - Mohit Kumar 001; Bernhard Moser 001; Lukas Fischer 001; Bernhard Freudenthaler (DEXA Workshops, 2021)

Membership-Mappings for Data Representation Learning: A Bregman Divergence Based Conditionally Deep Autoencoder. - Mohit Kumar 001; Bernhard Moser 001; Lukas Fischer 001; Bernhard Freudenthaler (DEXA Workshops, 2021)

Robust and Efficient Bio-Inspired Data-Sampling Prototype for Time-Series Analysis. - Michael Lunglmayr; Günther Lindorfer; Bernhard Moser 001 (DEXA Workshops, 2021)

The balancing principle for parameter choice in distance-regularized domain adaptation. - Werner Zellinger; Natalia Shepeleva; Marius-Constantin Dinu; Hamid Eghbal-zadeh; Hoan Duc Nguyen; Bernhard Nessler; Sergei V. Pereverzyev; Bernhard Alois Moser (NeurIPS, 2021)

On generalization in moment-based domain adaptation. - Werner Zellinger; Bernhard Alois Moser; Susanne Saminger-Platz (Ann. Math. Artif. Intell., 2021)

On the truncated Hausdorff moment problem under Sobolev regularity conditions. - Werner Zellinger; Bernhard Alois Moser (Appl. Math. Comput., 2021)

Membership-Mappings for Data Representation Learning. - Mohit Kumar 001; Bernhard Alois Moser; Lukas Fischer 001; Bernhard Freudenthaler (CoRR, 2021)

Information Theoretic Evaluation of Privacy-Leakage, Interpretability, and Transferability for a Novel Trustworthy AI Framework. - Mohit Kumar 001; Bernhard Alois Moser; Lukas Fischer 001; Bernhard Freudenthaler (CoRR, 2021)

An optimal (∊, δ)-differentially private learning of distributed deep fuzzy models. - Mohit Kumar 001; Michael Rossbory; Bernhard Alois Moser; Bernhard Freudenthaler (Inf. Sci., 2021)

AI System Engineering - Key Challenges and Lessons Learned. - Lukas Fischer 001; Lisa Ehrlinger; Verena Geist; Rudolf Ramler; Florian Sobieczky; Werner Zellinger; David Brunner; Mohit Kumar 001; Bernhard Moser 001 (Mach. Learn. Knowl. Extr., 2021)

Towards Practical Secure Privacy-Preserving Machine (Deep) Learning with Distributed Data. - Mohit Kumar 001; Bernhard Moser 001; Lukas Fischer 001; Bernhard Freudenthaler (DEXA Workshops, 2022)

Unboundedness of Linear Regions of Deep ReLU Neural Networks. - Anton Ponomarchuk; Christoph Koutschan; Bernhard Moser 001 (DEXA Workshops, 2022)

A Comparative Analysis of Anomaly Detection Methods for Predictive Maintenance in SME. - Muhammad Qasim; Maqbool Khan; Waqar Mehmood; Florian Sobieczky; Mario Pichler; Bernhard Moser 001 (DEXA Workshops, 2022)

Towards a Reference Software Architecture for Human-AI Teaming in Smart Manufacturing. - Philipp Haindl; Georg Buchgeher; Maqbool Khan; Bernhard Moser 001 (ICSE (NIER), 2022)

Teaming.AI: Enabling Human-AI Teaming Intelligence in Manufacturing. - Thomas Hoch; Bernhard Heinzl; Gerald Czech; Maqbool Khan; Philipp Waibel; Stefan Bachhofner; Elmar Kiesling; Bernhard Moser 001 (I-ESA Workshops, 2022)

Tessellation-Filtering ReLU Neural Networks. - Bernhard Alois Moser; Michal Lewandowski; Somayeh Kargaran; Werner Zellinger; Battista Biggio; Christoph Koutschan (IJCAI, 2022)

A Systematic Mapping Study of Predictive Maintenance in SMEs. - Maqbool Khan; Arshad Ahmad 002; Florian Sobieczky; Mario Pichler; Bernhard Alois Moser; Ivo Bukovsky (IEEE Access, 2022)

Special Issue on Machine Learning and Knowledge Graphs. - Mehwish Alam; Anna Fensel; Jorge Martinez-Gil; Bernhard Moser 001; Diego Reforgiato Recupero; Harald Sack (Future Gener. Comput. Syst., 2022)

Measuring Overhead Costs of Federated Learning Systems by Eavesdropping. - Rainer Meindl; Bernhard Alois Moser (DEXA Workshops, 2023)

Secure Federated Learning with Kernel Affine Hull Machines. - Mohit Kumar 001; Bernhard Moser 001; Lukas Fischer 001 (ESANN, 2023)

Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. - Marius-Constantin Dinu; Markus Holzleitner; Maximilian Beck; Hoan Duc Nguyen; Andrea Huber; Hamid Eghbal-zadeh; Bernhard Alois Moser; Sergei V. Pereverzyev; Sepp Hochreiter; Werner Zellinger (ICLR, 2023)

An Information Theoretic Approach to Privacy-Preserving Interpretable and Transferable Learning. - Mohit Kumar 001; Bernhard Alois Moser; Lukas Fischer 001; Bernhard Freudenthaler (Algorithms, 2023)

Kernel Affine Hull Machines for Differentially Private Learning. - Mohit Kumar 001; Bernhard Alois Moser; Lukas Fischer 001 (CoRR, 2023)

Quantization in Spiking Neural Networks. - Bernhard Alois Moser; Michael Lunglmayr (CoRR, 2023)

Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning. - Antonio Emanuele Cinà; Kathrin Grosse; Ambra Demontis; Sebastiano Vascon; Werner Zellinger; Bernhard Alois Moser; Alina Oprea; Battista Biggio; Marcello Pelillo; Fabio Roli (ACM Comput. Surv., 2023)

Integrate-and-Fire from a Mathematical and Signal Processing Perspective. - Bernhard Alois Moser; Anna Werzi; Michael Lunglmayr (IEEECONF, 2024)

SNN Architecture for Differential Time Encoding Using Decoupled Processing Time. - Daniel Windhager; Bernhard Alois Moser; Michael Lunglmayr (AICAS, 2024)

Risk Assessment in AI System Engineering: Experiences and Lessons Learned from a Practitioner's Perspective. - Magdalena Fuchs; Lukas Fischer 001; Alessio Montuoro; Mohit Kumar 001; Bernhard Alois Moser (DEXA Workshops, 2024)

On the Solvability of the XOR Problem by Spiking Neural Networks. - Bernhard Alois Moser; Michael Lunglmayr (DEXA Workshops, 2024)

Influence of Spike Encoding, Neuron Models and Quantization on SNN Performance. - Daniel Windhager; Bernhard Moser 001; Michael Lunglmayr (EUROCAST (2), 2024)

On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach (Abstract Reprint). - Mohit Kumar 001; Bernhard Alois Moser; Lukas Fischer 001 (IJCAI, 2024)

Towards Integrating Knowledge Graphs into Process-Oriented Human-AI Collaboration in Industry. - Bernhard Heinzl; Agastya Silvina; Franz Krause; Nicole Schwarz; Kabul Kurniawan; Elmar Kiesling; Mario Pichler; Bernhard Moser 001 (SWQD, 2024)

On Leaky-Integrate-and Fire as Spike-Train-Quantization Operator on Dirac-Superimposed Continuous-Time Signals. - Bernhard Alois Moser; Michael Lunglmayr (CoRR, 2024)

On the Sampling Sparsity of Neuromorphic Analog-to-Spike Conversion based on Leaky Integrate-and-Fire. - Bernhard Alois Moser; Michael Lunglmayr (CoRR, 2024)

CantorNet: A Sandbox for Testing Geometrical and Topological Complexity Measures. - Michal Lewandowski; Hamid Eghbalzadeh; Bernhard Alois Moser (CoRR, 2024)

Managing human-AI collaborations within Industry 5.0 scenarios via knowledge graphs: key challenges and lessons learned. - Franz Krause; Heiko Paulheim; Elmar Kiesling; Kabul Kurniawan; Maria Chiara Leva; Hector Diego Estrada-Lugo; Gernot Stübl; Nazim Kemal Üre; Javier Dominguez-Ledo; Maqbool Khan; Pedro Demolder; Hans Gaux; et al. (Frontiers Artif. Intell., 2024)

Spiking neural networks in the Alexiewicz topology: A new perspective on analysis and error bounds. - Bernhard Alois Moser; Michael Lunglmayr (Neurocomputing, 2024)

On Mitigating the Utility-Loss in Differentially Private Learning: A New Perspective by a Geometrically Inspired Kernel Approach. - Mohit Kumar 001; Bernhard Alois Moser; Lukas Fischer 001 (J. Artif. Intell. Res., 2024)

Rethinking data augmentation for adversarial robustness. - Hamid Eghbal-zadeh; Werner Zellinger; Maura Pintor; Kathrin Grosse; Khaled Koutini; Bernhard Alois Moser; Battista Biggio; Gerhard Widmer (Inf. Sci., 2024)

A Hardware Architecture for Efficient Adaptive Threshold-Based Sampling using Weyl's Discrepancy. - Anna Werzi; Simon Dorrer; Bernhard Alois Moser; Michael Lunglmayr (ISCAS, 2025)

Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent. - Mohit Kumar 001; Alexander Valentinitsch; Magdalena Fuchs; Mathias Brucker; Juliana Bowles; Adnan Husakovic; Ali Abbas; Bernhard Moser 001 (J. Artif. Intell. Res., 2025)

On Space Folds of ReLU Neural Networks. - Michal Lewandowski; Hamid Eghbalzadeh; Bernhard Heinzl; Raphael Pisoni; Bernhard Alois Moser (Trans. Mach. Learn. Res., 2025)

Spiking Neural Network Accelerator Architecture for Differential-Time Representation using Learned Encoding. - Daniel Windhager; Lothar Ratschbacher; Bernhard Moser 001; Michael Lunglmayr (CoRR, 2025)

The Space Between: On Folding, Symmetries and Sampling. - Michal Lewandowski; Bernhard Heinzl; Raphael Pisoni; Bernhard Alois Moser (CoRR, 2025)

Lightweight LIF-only SNN accelerator using differential time encoding. - Daniel Windhager; Lothar Ratschbacher; Bernhard Alois Moser; Michael Lunglmayr (CoRR, 2025)

Representing piecewise linear functions by functions with small arity. - Christoph Koutschan; Bernhard Moser 001; Anton Ponomarchuk; Josef Schicho (Appl. Algebra Eng. Commun. Comput., 2025)