Stuckenschmidt, Heiner

1. Reinforced Anytime Bottom Up Rule Learning for Knowledge Graph Completion
   2020/04/09 by Christian Meilicke, Meilicke, Christian, Melisachew Wudage Chekol +5 · 5 citations
   Computer Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Bayesian Modeling and Causal Inference #FOS: Computer and information sciences #Machine Learning (cs.LG) #Topic Modeling
2. TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
   2024/06/14 by Julia Gastinger, Gastinger, Julia, Shenyang Huang +21 · 12 citations
   Computer Science · Decision Sciences · #Advanced Graph Neural Networks #Data Quality and Management #FOS: Computer and information sciences #Graph Theory and Algorithms #Machine Learning (cs.LG) #Social and Information Networks (cs.SI)
3. Political Text Scaling Meets Computational Semantics
   2019/04/12 by Federico Nanni, Nanni, Federico, Goran Glavašš +7 · 2 citations
   Physics and Astronomy · Social Sciences · #Computation and Language (cs.CL) #Computational and Text Analysis Methods #FOS: Computer and information sciences #Opinion Dynamics and Social Influence #Social Media and Politics
4. PGTNet: A Process Graph Transformer Network for Remaining Time Prediction of Business Process Instances
   2024/04/09 by Elyasi, Keyvan Amiri, van der Aa, Han, Stuckenschmidt, Heiner · 4 citations
   #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Machine Learning (cs.LG)
5. Neural Architecture Performance Prediction Using Graph Neural Networks
   2020/10/19 by Lukasik, Jovita, Friede, David, Stuckenschmidt, Heiner +1 · 2 citations
   #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences
6. AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation
   2024/08/16 by Lukas Kirchdorfer, Kirchdorfer, Lukas, Robert Blümel +7 · 4 citations
   Business, Management and Accounting · #Artificial Intelligence (cs.AI) #Business Process Modeling and Analysis #FOS: Computer and information sciences #Multiagent Systems (cs.MA)
7. GRANDE: Gradient-Based Decision Tree Ensembles for Tabular Data
   2023/09/29 by Sascha Marton, Stefan Lüdtke, Marton, Sascha +5 · 2 citations
   Computer Science · #AI in cancer detection #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning in Healthcare
8. Unreflected Use of Tabular Data Repositories Can Undermine Research Quality
   2025/03/12 by Andrej Tschalzev, Lennart Purucker, Tschalzev, Andrej +9 · 5 citations
   Business, Management and Accounting · Computer Science · #Big Data and Business Intelligence #FOS: Computer and information sciences #Machine Learning (cs.LG) #Research Data Management Practices
9. A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data
   2024/07/02 by Andrej Tschalzev, Sascha Marton, Tschalzev, Andrej +7 · 2 citations
   Computer Science · Engineering · #Advanced Data Processing Techniques #Artificial Intelligence (cs.AI) #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning and Data Classification
10. History repeats Itself: A Baseline for Temporal Knowledge Graph Forecasting
    2024/04/25 by Gastinger, Julia, Meilicke, Christian, Errica, Federico +3 · 2 citations
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
11. Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
    2024/08/16 by Marton, Sascha, Grams, Tim, Vogt, Florian +3 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)