Prognose und Asymptotik Bayesscher Modelle: e. Methode zur Evaluation d. Genauigkeit ökonometr. Prognosen. - Gerhard Paaß (Oldenbourg, 1984)

Anonymität von Individualdaten in statistischen Datenbanken. - Gerhard Paass (Datenschutz und Datensicherung, 1985)

Bayesian Integration of Uncertain and Conflicting Evidence. - Gerhard Paass (GWAI, 1989)

Probabilistic Default Reasoning. - Gerhard Paass (IPMU, 1990)

A Stochastic EM Learning Algorithm for Structured Probabilistic Neural Networks. - Gerhard Paass (ÖGAI, 1990)

Second order probabilities for uncertain and conflicting evidence. - Gerhard Paass (UAI, 1990)

Probabilistic Default Reasoning Involving Continous Variables. - Gerhard Paass (ECSQARU, 1991)

Integrating Probabilistic Rules into Neural Networks: A Stochastic EM Learning Algorithm. - Gerhard Paass (UAI, 1991)

Assessing and Improving Neural Network Predictions by the Bootstrap Algorithm. - Gerhard Paass (NIPS, 1992)

MESA: Maximum Entropy by Simulated Annealing. - Gerhard Paass (UAI, 1992)

European Conference on Symbolic and Quantitative Approaches for Uncertainty. - Jochen Heinsohn; Gerhard Paass (Künstliche Intell., 1992)

Wissensverarbeitung mit neuronalen Netzen. - Gerhard Paass; Franz J. Kurfess (KI, 1993)

Bericht von der Konferenz "Neural Information Processing Szstems - Natural and Synthetic" (NIPS) 1992. - Alexander Linden 002; Gerhard Paass (Künstliche Intell., 1993)

Bayesian Query Construction for Neural Network Models. - Gerhard Paass; Jörg Kindermann (NIPS, 1994)

Künstliche Neuronale Netze: eine Bestandsaufnahme. - Knut Möller; Gerhard Paass (Künstliche Intell., 1994)

Estimating Blue-Green Algae Counts with Neurocomputing Techniques. - Joachim Diederich; Don Simonetta; Gerhard Paass (IEA/AIE, 1995)

From Recombination of Genes to the Estimation of Distributions I. Binary Parameters. - Heinz Mühlenbein; Gerhard Paass (PPSN, 1996)

Bayesian Classification Trees with Overlapping Leaves Applied to Credit-Scoring. - Gerhard Paass; Jörg Kindermann (PAKDD, 1998)

Model Switching for Bayesian Classification Trees with Soft Splits. - Jörg Kindermann; Gerhard Paass (PKDD, 1998)

Klassifikation mit Populationen von heterogenen Modellen. - Gerhard Paass; Jörg Kindermann (Künstliche Intell., 1998)

Convergence properties of incremental Bayesian evolutionary algorithms with single Markov chains. - Byoung-Tak Zhang; Gerhard Paass; Heinz Mühlenbein (CEC, 2000)

Multistep Sequential Exploration of Growing Bayesian Classification Models. - Gerhard Paass; Jörg Kindermann (IJCNN (3), 2000)

Transparency and Predicive Power: Explaining Complex Classification Models. - Gerhard Paass; Jörg Kindermann (PKDD, 2000)

Error Correcting Codes with Optimized Kullback-Leibler Distances for Text Categorization. - Jörg Kindermann; Gerhard Paass; Edda Leopold (PKDD, 2001)

Exploring sub-word features and linear support vector machines for German spoken document classification. - Martha A. Larson; Stefan Eickeler; Gerhard Paaß; Edda Leopold; Jörg Kindermann (INTERSPEECH, 2002)

SVM Classification Using Sequences of Phonemes and Syllables. - Gerhard Paass; Edda Leopold; Martha A. Larson; Jörg Kindermann; Stefan Eickeler (PKDD, 2002)

Authorship Attribution with Support Vector Machines. - Joachim Diederich; Jörg Kindermann; Edda Leopold; Gerhard Paass (Appl. Intell., 2003)

Bayesian regression mixtures of experts for geo-referenced data. - Gerhard Paass; Jörg Kindermann (Intell. Data Anal., 2003)

Learning Prototype Ontologies by Hierachical Latent Semantic Analysis. - Gerhard Paaß; Jörg Kindermann; Edda Leopold (LWA, 2004)

Revealing the connoted visual code: a new approach to video classification. - René Cavet; Stephan Volmer; Edda Leopold; Jörg Kindermann; Gerhard Paaß (Comput. Graph., 2004)

Evaluating the Performance of Text Mining Systems on Real-world Press Archives. - Gerhard Paaß; Hugo de Vries (GfKl, 2005)

A Brief Survey of Text Mining. - Andreas Hotho; Andreas Nürnberger; Gerhard Paass (LDV Forum, 2005)

Analysis of E-Discussions Using Classifier Induced Semantic Spaces. - Edda Leopold; Jörg Kindermann; Gerhard Paaß (LDV Forum, 2007)

Improved Phishing Detection using Model-Based Features. - André Bergholz; Jeong Ho Chang; Gerhard Paass; Frank Reichartz; Siehyun Strobel (CEAS, 2008)

Detecting Known and New Salting Tricks in Unwanted Emails. - André Bergholz; Gerhard Paass; Frank Reichartz; Siehyun Strobel; Marie-Francine Moens; Brian Witten (CEAS, 2008)

Anticipating Hidden Text Salting in Emails. - Christina Lioma; Marie-Francine Moens; Juan-Carlos Gomez 001; Jan De Beer; André Bergholz; Gerhard Paass; Patrick Horkan (RAID, 2008)

Composite Kernels For Relation Extraction. - Frank Reichartz; Hannes Korte; Gerhard Paass (ACL/IJCNLP (2), 2009)

A Logic-Based Approach to Relation Extraction from Texts. - Tamás Horváth 001; Gerhard Paass; Frank Reichartz; Stefan Wrobel (ILP, 2009)

Named Entity Resolution Using Automatically Extracted Semantic Information. - Anja Pilz; Gerhard Paaß (LWA, 2009)

Dependency Tree Kernels for Relation Extraction from Natural Language Text. - Frank Reichartz; Hannes Korte; Gerhard Paass (ECML/PKDD (2), 2009)

Exploiting Semantic Constraints for Estimating Supersenses with CRFs. - Gerhard Paaß; Frank Reichartz (SDM, 2009)

Named Entity Recognition of Spoken Documents Using Subword Units. - Gerhard Paass; Anja Pilz; Jochen Schwenninger (ICSC, 2009)

Semantic relation extraction with kernels over typed dependency trees. - Frank Reichartz; Hannes Korte; Gerhard Paass (KDD, 2010)

New filtering approaches for phishing email. - André Bergholz; Jan De Beer; Sebastian Glahn; Marie-Francine Moens; Gerhard Paaß; Siehyun Strobel (J. Comput. Secur., 2010)

From names to entities using thematic context distance. - Anja Pilz; Gerhard Paaß (CIKM, 2011)

Future trends in business analytics and optimization. - Donald E. Brown; Fazel Famili; Gerhard Paass; Kate Smith-Miles; Lyn C. Thomas; Richard Weber 002; Ricardo Baeza-Yates; Cristián Bravo; Gaston L'Huillier; Sebastián Maldonado (Intell. Data Anal., 2011)

Collective Search for Concept Disambiguation. - Anja Pilz; Gerhard Paaß (COLING, 2012)

A knowledge-extraction approach to identify and present verbatim quotes in free text. - Gerhard Paaß; André Bergholz; Anja Pilz (I-KNOW, 2012)

Machine Learning for Document Structure Recognition. - Gerhard Paaß; Iuliu Vasile Konya (Modeling, Learning, and Processing of Text Technological Data Structures, 2012)

Linguistics to Structure Unstructured Information. - Günter Neumann; Gerhard Paaß; David van den Akker (Towards the Internet of Services, 2014)

Grundlagen des Maschinellen Lernens. - Christian Bauckhage; Wolfgang Hübner 001; Ronny Hug; Gerhard Paaß; Stefan Rüping 001 (Handbuch der Künstlichen Intelligenz, 2020)

Tiefe neuronale Netze. - Christian Bauckhage; Wolfgang Hübner 001; Ronny Hug; Gerhard Paaß (Handbuch der Künstlichen Intelligenz, 2020)

Vertrauenswürdiges, transparentes und robustesMaschinelles Lernen. - Christian Bauckhage; Johannes Fürnkranz; Gerhard Paaß (Handbuch der Künstlichen Intelligenz, 2020)

Foundation Models for Natural Language Processing - Pre-trained Language Models Integrating Media. - Gerhard Paaß; Sven Giesselbach (CoRR, 2023)

Foundation Models for Natural Language Processing - Pre-trained Language Models Integrating Media - Gerhard Paaß; Sven Giesselbach (Springer, 2023)

Big Data 2.0 - mit synthetischen Daten KI-Systeme stärken. - Dirk Hecker; Angi Voss; Gerhard Paaß; Tim Wirtz (Wirtschaftsinformatik Manag., 2023)

Artificial Intelligence - What Is Behind the Technology of the Future? - Gerhard Paaß (Springer, 2024)