Publications

See also my Google Scholar profile.

2026

G-RRM: Guiding Symbolic Solvers with Recurrent Reasoning Models

Timo Bertram, Sidhant Bhavnani, Richard Freinschlag, Erich Kobler, Andreas Mayr, Günter Klambauer

NeSy 2026 — 20th International Conference on Neural-Symbolic Learning and Reasoning

RePAIR: Predictive Self-Supervised Representation Learning in Chess

Christoph Koller, Johannes Fürnkranz, Timo Bertram

IEEE Conference on Games (CoG) 2026

Toxicity in Twitch Chats: An LLM-Based Analysis Across Gaming Communities

Ronja Fuchs, Florian Rupp, Timo Bertram, Kai Eckert, Alexander Dockhorn

IEEE Conference on Games (CoG) 2026

Symbol-Equivariant Recurrent Reasoning Models

Richard Freinschlag, Timo Bertram, Erich Kobler, Andreas Mayr, Günter Klambauer

ICML 2026 — 43rd International Conference on Machine Learning

2025

Drafting “Magic: The Gathering” With High-Dimensional Card Embeddings

Timo Bertram, Johannes Fürnkranz, Martin Müller

IEEE Transactions on Games

Deceptive Game Design? Investigating the Impact of Visual Card Style on Player Perception

Leonie Kallabis, Timo Bertram, Florian Rupp

IEEE Conference on Games (CoG) 2025

UrzaGPT: LoRA-Tuned Large Language Models for Card Selection in Collectible Card Games

Timo Bertram

arXiv preprint

2024

Neural Network-based Information Set Weighting for Playing Reconnaissance Blind Chess

Timo Bertram, Johannes Fürnkranz, Martin Müller

IEEE Transactions on Games

Contrastive Learning of Preferences with a Contextual InfoNCE Loss

Timo Bertram, Johannes Fürnkranz, Martin Müller

arXiv preprint

Efficiently Training Neural Networks for Imperfect Information Games by Sampling Information Sets

Timo Bertram, Johannes Fürnkranz, Martin Müller

KI 2024: Advances in Artificial Intelligence

Learning With Generalised Card Representations for “Magic: The Gathering”

Timo Bertram, Johannes Fürnkranz, Martin Müller

IEEE Conference on Games (CoG) 2024 — best student paper award

Contrastive Learning for Imperfect Information Games

Timo Bertram

PhD thesis, Johannes Kepler University Linz

2023

The Machine Reconnaissance Blind Chess Tournament of NeurIPS 2022

Ryan W. Gardner, Gino Perrotta, Anvay Shah, Shivaram Kalyanakrishnan, Kevin A. Wang, Gregory Clark, Timo Bertram, Johannes Fürnkranz, Martin Müller, Brady P. Garrison, Prithviraj Dasgupta, Saeid Rezaei

NeurIPS 2022 Competition Track

Weighting Information Sets with Siamese Neural Networks in Reconnaissance Blind Chess

Timo Bertram, Johannes Fürnkranz, Martin Müller

IEEE Conference on Games (CoG) 2023

2022

Supervised and Reinforcement Learning from Observations in Reconnaissance Blind Chess

Timo Bertram, Johannes Fürnkranz, Martin Müller

IEEE Conference on Games (CoG) 2022

Quantity vs Quality: Investigating the Trade-Off between Sample Size and Label Reliability

Timo Bertram, Johannes Fürnkranz, Martin Müller

arXiv preprint

2021

A Comparison of Contextual and Non-Contextual Preference Ranking for Set Addition Problems

Timo Bertram, Johannes Fürnkranz, Martin Müller

ICML 2021 SubsetML Workshop

Predicting Human Card Selection in Magic: The Gathering with Contextual Preference Ranking

Timo Bertram, Johannes Fürnkranz, Martin Müller

IEEE Conference on Games (CoG) 2021 — best paper award