Dr. Marc Finthammer

E-Mail: marc.finthammer

Telefon: +49 2331 987 - 4119

Fax: +49 2331 987 - 317

Raum: Gebäude 3 (Informatikzentrum), 3. Etage, Block I, Raum 09

Veröffentlichungen

  • J. Desel & M. Finthammer, "Stop-transitions of Petri Nets", Fundam. Informaticae 175(1-4), 143-172 (2020)
  • J. Desel, M. Finthammer & A. Frank, "Cyclon - A Tool for Determining Stop-Transitions of Petri Nets", Application and Theory of Petri Nets and Concurrency - 41st International Conference, PETRI NETS 2020 12152, 392-402 (2020)
  • M. Finthammer, "Concepts and Algorithms for Computing Maximum Entropy Distributions for Knowledge Bases with Relational Probabilistic Conditionals", KI - Künstliche Intelligenz 33, 97-100 (2019)
  • M. Wilhelm, G. Kern-Isberner, M. Finthammer & C. Beierle, "Integrating Typed Model Counting into First-Order Maximum Entropy Computations and the Connection to Markov Logic Networks", 494-499 (2019)
  • M. Wilhelm, G. Kern-Isberner, M. Finthammer & C. Beierle, "A Generalized Iterative Scaling Algorithm for Maximum Entropy Model Computations Respecting Probabilistic Independencies", 10833, 379-399 (2018)
  • M. Finthammer, "Concepts and Algorithms for Computing Maximum Entropy Distributions for Knowledge Bases with Relational Probabilistic Conditionals", 342, (2017)
  • M. Finthammer, "Concepts and Algorithms for Computing Maximum Entropy Distributions for Knowledge Bases with Relational Probabilistic Conditionals", (2016)
  • M. Finthammer & C. Beierle, "On the Relationship Between Aggregating Semantics and FO-PCL Grounding Semantics for Relational Probabilistic Conditionals", 29, 297-315 (2016)
  • C. Beierle, M. Finthammer & G. Kern-Isberner, "Relational Probabilistic Conditionals and Their Instantiations under Maximum Entropy Semantics for First-Order Knowledge Bases", Entropy 17, 852-865 (2015) PDF
  • C. Beierle, G. Kern-Isberner, M. Finthammer & N. Potyka, "Extending and Completing Probabilistic Knowledge and Beliefs Without Bias", KI - Künstliche Intelligenz 29, 255-262 (2015)
  • C. Beierle, S. Kuche, M. Finthammer & G. Kern-Isberner, "A Software System for the Computation, Visualization, and Comparison of Conditional Structures for Relational Probabilistic Knowledge Bases", 558-563 (2015)
  • C. Beierle, N. Potyka, J. Baudisch & M. Finthammer, "Towards Lifted Inference under Maximum Entropy for Probabilistic Relational FO-PCL Knowledge Bases", 506-516 (2015)
  • M. Finthammer & C. Beierle, "Towards a More Efficient Computation of Weighted Conditional Impacts for Relational Probabilistic Knowledge Bases under Maximum Entropy Semantics", 72-86 (2015) PDF
  • M. Finthammer & C. Beierle, "A Two-Level Approach to Maximum Entropy Model Computation for Relational Probabilistic Logic Based on Weighted Conditional Impacts", 8720, 162-175 (2014)
  • C. Beierle, M. Finthammer, N. Potyka, J. Varghese & G. Kern-Isberner, "A Case Study on the Application of Probabilistic Conditional Modelling and Reasoning to Clinical Patient Data in Neurosurgery", 7958, 49-60 (2013)
  • M. Finthammer, "A Generalized Iterative Scaling Algorithm for Maximum Entropy Reasoning in Relational Probabilistic Conditional Logic Under Aggregation Semantics", (2012)
  • M. Finthammer, "An Iterative Scaling Algorithm for Maximum Entropy Reasoning in Relational Probabilistic Conditional Logic", 7520, 351-364 (2012)
  • M. Finthammer & C. Beierle, "How to Exploit Parametric Uniformity for Maximum Entropy Reasoning in a Relational Probabilistic Logic", 7519, 189-201 (2012)
  • M. Finthammer & C. Beierle, "Using Equivalences of Worlds for Aggregation Semantics of Relational Conditionals", 7526, 49-60 (2012)
  • M. Finthammer & C. Beierle, "Instantiation Restrictions for Relational Probabilistic Conditionals", 7520, 598-605 (2012)
  • M. Finthammer, R. Masternak & C. Beierle, "Biomedical Diagnosis Based on Ion Mobility Spectrometry -- A Case Study Using Probabilistic Relational Modelling and Learning", 300, 665-675 (2012)
  • M. Finthammer & M. Thimm, "An Integrated Development Environment for Probabilistic Relational Reasoning", Logic Journal of the IGPL 20, 831-871 (2012)
  • G. Kern-Isberner, C. Beierle, M. Finthammer & M. Thimm, "Comparing and Evaluating Approaches to Probabilistic Reasoning: Theory, Implementation, and Applications", Transactions on Large-Scale Data- and Knowledge-Centered Systems 6, 31-75 (2012)
  • C. Beierle, M. Finthammer, G. Kern-Isberner & M. Thimm, "Evaluation and Comparison Criteria for Approaches to Probabilistic Relational Knowledge Representation", 7006, 63-74 (2011)
  • M. Finthammer & N. Potyka, "Learning Scenarios under Relational Probabilistic Semantics and ME Reasoning", 46-60 (2011)
  • G. Kern-Isberner, C. Beierle, M. Finthammer & M. Thimm, "Probabilistic Logics in Expert Systems: Approaches, Implementations, and Applications", 6860, 27-46 (2011)
  • C. Beierle, M. Finthammer, G. Kern-Isberner & M. Thimm, "Automated Reasoning for Relational Probabilistic Knowledge Representation", 6173, 218-224 (2010)
  • M. Finthammer, C. Beierle, J. Fisseler, G. Kern-Isberner & J. I. Baumbach, "Using Probabilistic Relational Learning to Support Bronchial Carcinoma Diagnosis Based on Ion Mobility Spectrometry", International Journal for Ion Mobility Spectrometry (IMS) 13, 83-93 (2010)
  • M. Finthammer, C. Beierle, J. Fisseler, G. Kern-Isberner, B. Möller & J. I. Baumbach, "Probabilistic Relational Learning for Medical Diagnosis Based on Ion Mobility Spectrometry", 80, 365-375 (2010)
  • M. Thimm, M. Finthammer, S. Loh, G. Kern-Isberner & C. Beierle, "A System for Relational Probabilistic Reasoning on Maximum Entropy", 116-121 (2010)
  • M. Finthammer, C. Beierle, B. Berger & G. Kern-Isberner, "Probabilistic Reasoning at Optimum Entropy with the MEcore System", 535-540 (2009)
  • M. Finthammer, C. Beierle, B. Berger & G. Kern-Isberner, "An Implementation of Belief Change Operations Based on Probabilistic Conditional Logic", 5753, 496-501 (2009)
  • M. Finthammer, S. Loh & M. Thimm, "Towards a Toolbox for Relational Probabilistic Knowledge Representation, Reasoning, and Learning", 34-48 (2009)
  • G. Kern-Isberner, M. Thimm, M. Finthammer & J. Fisseler, "Mining Default Rules From Statistical Data", (2009)
  • I. Cramer & M. Finthammer, "An Evaluation Procedure for Word Net Based Lexical Chaining: Methods and Issues", 120-146 (2008)
  • I. Cramer & M. Finthammer, "Tools for exploring GermaNet in the context of CL-teaching", 195-208 (2008)
  • I. Cramer, M. Finthammer, A. Kurek, L. Sowa, M. Wachtling & T. Claas, "Experiments on Lexical Chaining for German Corpora: Annotation, Extraction, and Application", Journal for Language Technology and Computational Linguistics (JLCL) 23, 34-48 (2008) PDF
  • M. Finthammer & I. Cramer, "Exploring and Navigating: Tools for GermaNet", (2008)
  • G. Kern-Isberner, M. Thimm & M. Finthammer, "Qualitative Knowledge Discovery", 4925, 88-113 (2008)
  • M. Finthammer, G. Kern-Isberner & M. Ritterskamp, "Resolving Inconsistencies in Probabilistic Knowledge Bases", 4667, 114-128 (2007)
  • M. Finthammer, "Entwicklung und Implementierung von Heuristiken zur Behandlung von Inkonsistenzen in probabilistischen Wissensbasen mit Anwendungen im Bereich der Wirtschaftsprüfung", (2006)
Lehrgebiet STTP | 10.05.2024