relAI research will be featured at the International Conference on Learning Representations (ICLR), which will take place this year at the Riocentro Convention and Event Center in Rio de Janeiro, Brazil, from April 23rd to 27th, 2026. ICLR is one of the leading conferences with significant impact and reputation in machine learning and artificial intelligence research.
relAI Publications at ICLR
- Seventeen publications from relAI will be presented at the conference, fifteen of them in the main track.
- Two of the relAI papers have been selected for presentation in the Journal-to-Conference Track. Those papers, titled Adversarial Robustness of Graph Transformers and Online Selective Conformal Prediction: Errors and Solutions, were previously published in the Transactions on Machine Learning Research (TMLR) journal.
Meet relAI Students
If you attend ICLR, be sure to take the opportunity to discuss relAI research with relAI students attending the conference: Sarah Ball, Cecilia Casolo, Lukas Gosch, Valentyn Melnychuk, Ole Petersen, Yusuf Sale, Yan Scholten, Jonas von Berg, and Jingpei Wu. You can find their research papers in the list below.
Full list of relAI publications at ICLR 2026:
- Efficient Credal Prediction through Decalibration
Paul Hofman, Timo Löhr, Maximilian Muschalik, Yusuf Sale, Eyke Hüllermeier - Discrete Bayesian Sample Inference for Graph Generation
Ole Petersen, Marcel Kollovieh, Marten Lienen, Stephan Günnemann - Identifiability Challenges in Sparse Linear Ordinary Differential Equations
Cecilia Casolo, Sören Becker, Niki Kilbertus - Sampling-aware Adversarial Attacks Against Large Language Models
Tim Beyer, Yan Scholten, Leo Schwinn, Stephan Günnemann - Model Collapse Is Not a Bug but a Feature in Machine Unlearning for LLMs
Yan Scholten, Sophie Xhonneux, Leo Schwinn, Stephan Günnemann - Efficient and Sharp Off-Policy Learning under Unobserved Confounding
Konstantin Hess, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel - Overlap-Adaptive Regularization for Conditional Average Treatment Effect Estimation
Valentyn Melnychuk, Dennis Frauen, Jonas Schweisthal, Stefan Feuerriegel - GDR-learners: Orthogonal Learning of Generative Models for Potential Outcomes
Valentyn Melnychuk, Stefan Feuerriegel - IGC-Net for conditional average potential outcome estimation over time
Konstantin Hess, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel - On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignment
Sarah Ball, Greg Gluch, Shafi Goldwasser, Frauke Kreuter, Omer Reingold, Guy N. Rothblum - Foundation Models for Causal Inference via Prior-Data Fitted Networks
Yuchen Ma, Dennis Frauen, Emil Javurek, Stefan Feuerriegel - An Orthogonal Learner for Individualized Outcomes in Markov Decision Processes
Emil Javurek, Valentyn Melnychuk, Jonas Schweisthal, Konstantin Hess, Dennis Frauen, Stefan Feuerriegel - The Price of Robustness: Stable Classifiers Need Overparameterization
Jonas von Berg, Adalbert Fono, Massimiliano Datres, Sohir Maskey, Gitta Kutyniok
Main Track
- Adversarial Robustness of Graph Transformers
Philipp Foth, Simon Geisler, Lukas Gosch, Leo Schwinn, Stephan Günnemann
Transactions on Machine Learning Research (TMLR), Journal Track Poster - ICLR 2026, 2025 - Online Selective Conformal Prediction: Errors and Solutions
Yusuf Sale, Aaditya Ramdas
Transactions on Machine Learning Research (TMLR), Journal Track Poster - ICLR 2026, 2025
Journal Track
- Exact Certification of Neural Networks and Partition Aggregation Ensembles against Label Poisoning
Ajinkya Mohgaonkar, Lukas Gosch, Mahalakshmi Sabanayagam, Debarghya Ghoshdastidar, Stephan Günnemann
ICLR 2026 Workshop on Principled Design for Trustworthy AI - ProcessThinker: Enhancing Multi-modal Large Language Models Reasoning via Rollout-based Process Reward
Jingpei Wu, Xiao Han, Weixiang Shen, Boer Zhang, Zifeng Ding, Volker Tresp
ICLR 2026 Workshop on Logical Reasoning of Large Language Models
Workshops
