A Simple Model for Sequences of Relational State Descriptions. - Ingo Thon; Niels Landwehr; Luc De Raedt (ECML/PKDD (2), 2008)

Relational Transformation-based Tagging for Activity Recognition. - Niels Landwehr; Bernd Gutmann; Ingo Thon; Luc De Raedt; Matthai Philipose (Fundam. Informaticae, 2008)

Don't Fear Optimality: Sampling for Probabilistic-Logic Sequence Models. - Ingo Thon (ILP, 2009)

An Exercise with Statistical Relational Learning Systems. - Maurice Bruynooghe; Daan Fierens; Bernd Gutmann; Angelika Kimmig; Niels Landwehr; Wannes Meert; Ingo Thon; Luc De Raedt (MLG/SRL@ILP, 2009)

DTProbLog: A Decision-Theoretic Probabilistic Prolog. - Guy Van den Broeck; Ingo Thon; Martijn van Otterlo; Luc De Raedt (AAAI, 2010)

Probabilistic Programming for Planning Problems. - Ingo Thon; Bernd Gutmann; Guy Van den Broeck (StarAI@AAAI, 2010)

Probabilistic Rule Learning. - Luc De Raedt; Ingo Thon (ILP, 2010)

Learning the Parameters of Probabilistic Logic Programs from Interpretations. - Bernd Gutmann; Ingo Thon; Luc De Raedt (ECML/PKDD (1), 2011)

Inference in Probabilistic Logic Programs using Weighted CNF's. - Daan Fierens; Guy Van den Broeck; Ingo Thon; Bernd Gutmann; Luc De Raedt (UAI, 2011)

Stochastic relational processes: Efficient inference and applications. - Ingo Thon; Niels Landwehr; Luc De Raedt (Mach. Learn., 2011)

The magic of logical inference in probabilistic programming. - Bernd Gutmann; Ingo Thon; Angelika Kimmig; Maurice Bruynooghe; Luc De Raedt (Theory Pract. Log. Program., 2011)

Stochastic Relational Processes and Models: Learning and Reasoning (Stochastisch relationele processen en modellen: leren en redeneren). - Ingo Thon (2011)

A Particle Filter for Probabilistic Dynamic Relational Domains. - Davide Nitti 001; Tinne De Laet; McElory Hoffmann; Ingo Thon; Guy Van den Broeck; Luc De Raedt (StarAI@UAI, 2012)

MCMC Estimation of Conditional Probabilities in Probabilistic Programming Languages. - Bogdan Moldovan; Ingo Thon; Jesse Davis; Luc De Raedt (ECSQARU, 2013)

Extracting hierarchical data points and tables from scanned contracts. - Jan Stadermann; Stephan Symons; Ingo Thon (UIMA@GSCL, 2013)

Inducing Probabilistic Relational Rules from Probabilistic Examples. - Luc De Raedt; Anton Dries; Ingo Thon; Guy Van den Broeck; Mathias Verbeke (IJCAI, 2015)

Inference and learning in probabilistic logic programs using weighted Boolean formulas. - Daan Fierens; Guy Van den Broeck; Joris Renkens; Dimitar Sht. Shterionov; Bernd Gutmann; Ingo Thon; Gerda Janssens; Luc De Raedt (Theory Pract. Log. Program., 2015)

Knowledge Graph Constraints for Multi-label Graph Classification. - Martin Ringsquandl; Steffen Lamparter; Ingo Thon; Raffaello Lepratti; Peer Kröger (ICDM Workshops, 2016)

Configuration of Industrial Automation Solutions Using Multi-relational Recommender Systems. - Marcel Hildebrandt; Swathi Shyam Sunder; Serghei Mogoreanu; Ingo Thon; Volker Tresp; Thomas A. Runkler (ECML/PKDD (3), 2018)

A Recommender System for Complex Real-World Applications with Nonlinear Dependencies and Knowledge Graph Context. - Marcel Hildebrandt; Swathi Shyam Sunder; Serghei Mogoreanu; Mitchell Joblin; Akhil Mehta; Ingo Thon; Volker Tresp (ESWC, 2019)

Grasping Partially Occluded Objects Using Autoencoder-Based Point Cloud Inpainting. - Alexander Koebler; Ralf Gross; Florian Buettner 001; Ingo Thon (ECML/PKDD (6), 2022)

Facilitating Change Implementation for Continuous ML-Safety Assurance. - Chih-Hong Cheng; Nguyen Anh Vu Doan; Balahari Balu; Franziska Schwaiger; Emmanouil Seferis; Simon Burton 001; Yassine Qamsane; Ankit Shukla; Yinchong Yang; Zhiliang Wu; Andreas Hapfelmeier; Ingo Thon (CoRR, 2022)

Towards Safety Assurance of Uncertainty-Aware Reinforcement Learning Agents. - Felippe Schmoeller Roza; Simon Hadwiger; Ingo Thon; Karsten Roscher (SafeAI@AAAI, 2023)

Structured Verification of Machine Learning Models in Industrial Settings. - Sai Rahul Kaminwar; Jann Goschenhofer; Janek Thomas; Ingo Thon; Bernd Bischl (Big Data, 2023)

Through the Eyes of the Expert: Aligning Human and Machine Attention for Industrial AI. - Alexander Koebler; Christian Greisinger; Jan Paulus; Ingo Thon; Florian Buettner 001 (HCI (52), 2024)

MoRE-LLM: Mixture of Rule Experts Guided by a Large Language Model. - Alexander Koebler; Ingo Thon; Florian Buettner 001 (ICDM, 2024)

Explanatory Model Monitoring to Understand the Effects of Feature Shifts on Performance. - Thomas Decker 004; Alexander Koebler; Michael Lebacher; Ingo Thon; Volker Tresp; Florian Buettner 001 (KDD, 2024)

Incremental Uncertainty-aware Performance Monitoring with Active Labeling Intervention. - Alexander Koebler; Thomas Decker 004; Ingo Thon; Volker Tresp; Florian Buettner 001 (AISTATS, 2025)