Isabelle Kuhlmann

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 19

Top Topics

Approximate Reasoning

Answer Set Programming

Top Venues

Publications

Carl Corea, Isabelle Kuhlmann, Matthias Thimm, John Grant
Paraconsistent reasoning for inconsistency measurement in declarative process specifications. Inf. Syst. 122 (2024)
Sandra Hoffmann, Isabelle Kuhlmann, Matthias Thimm
Enhancing Abstract Argumentation Solvers with Machine Learning-Guided Heuristics: A Feasibility Study. RATIO (2024)
Lars Bengel, Lydia Blümel, Elfia Bezou-Vrakatseli, Federico Castagna, Giulia D'Agostino, Isabelle Kuhlmann, Jack Mumford, Daphne Odekerken, Fabrizio Russo, Stefan Sarkadi, Madeleine Waller, Andreas Xydis
Online Handbook of Argumentation for AI: Volume 4. CoRR (2024)
Jonas Klein, Isabelle Kuhlmann, Matthias Thimm
Cluster-Specific Rule Mining for Argumentation-Based Classification. RATIO (2024)
Isabelle Kuhlmann, Carl Corea, John Grant
An ASP-Based Framework for Solving Problems Related to Declarative Process Specifications. NMR (2023)
Isabelle Kuhlmann, Matthias Thimm
A Discussion of Challenges in Benchmark Generation for Abstract Argumentation. Arg&App@KR (2023)
Isabelle Kuhlmann, Andreas Niskanen, Matti Järvisalo
Computing MUS-Based Inconsistency Measures. JELIA (2023)
Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo, Matthias Thimm
Comparison of SAT-based and ASP-based Algorithms for Inconsistency Measurement. CoRR (2023)
Andreas Niskanen, Isabelle Kuhlmann, Matthias Thimm, Matti Järvisalo
MaxSAT-Based Inconsistency Measurement. ECAI (2023)
Isabelle Kuhlmann, Carl Corea, John Grant
Non-Automata Based Conformance Checking of Declarative Process Specifications Based on ASP. Business Process Management Workshops (2023)
Isabelle Kuhlmann, Thorsten Wujek, Matthias Thimm
On the Impact of Data Selection when Applying Machine Learning in Abstract Argumentation. COMMA (2022)
Jonas Klein, Isabelle Kuhlmann, Matthias Thimm
Graph Neural Networks for Algorithm Selection in Abstract Argumentation. ArgML@COMMA (2022)
Isabelle Kuhlmann, Anna Gessler, Vivien Laszlo, Matthias Thimm
A Comparison of ASP-Based and SAT-Based Algorithms for the Contension Inconsistency Measure. SUM (2022)
Isabelle Kuhlmann, Viktor Seib, Dietrich Paulus
Integrating Feedforward Design into a Generative Network to Synthesize Supplementary Training Data for Object Classification. ICARSC (2021)
Isabelle Kuhlmann, Tjitze Rienstra, Lars Bengel, Kenneth Skiba, Matthias Thimm
Distinguishability in Abstract Argumentation. KR (2021)
Isabelle Kuhlmann, Matthias Thimm
An Algorithm for the Contension Inconsistency Measure Using Reductions to Answer Set Programming. SUM (2020)
Isabelle Kuhlmann, Matthias Thimm
Using Graph Convolutional Networks for Approximate Reasoning with Abstract Argumentation Frameworks: A Feasibility Study. SUM (2019)
Raphael Memmesheimer, Isabelle Kuhlmann, Mark Mints, Patrik Schmidt, Christian Korbach, Ida Germann, Dietrich Paulus
Scratchy: A Lightweight Modular Autonomous Robot for Robotic Competitions. CoRR (2019)
Raphael Memmesheimer, Isabelle Kuhlmann, Mark Mints, Patrik Schmidt, Christian Korbach, Ida Germann, Dietrich Paulus
Scratchy: A Lightweight Modular Autonomous Robot for Robotic Competitions. ICARSC (2019)