Over 20 Hub papers accepted at ICLR 2026
The Erlangen Hub has achieved a significant international research milestone, with over 20 papers accepted at ICLR 2026, one of the world’s leading conferences in artificial intelligence and machine learning.
The International Conference on Learning Representations, known as ICLR, is a premier global venue for research in areas such as deep learning, reinforcement learning, and the theoretical foundations of modern AI, and will be held in Rio de Janeiro, Brazil, from Thursday 23 April to Monday 27 April.
ICLR 2026 had over 19,000 paper submissions from researchers worldwide, with an acceptance rate of only around 30 percent. For Erlangen, securing over 20 papers in a single year is an excellent outcome. This success ensures the Hub remains a productive contributor to the conference internationally and the wider AI research conversation.
The accepted papers are diverse. They span a wide range of topics at the forefront of AI research, reflecting both the breadth and depth of expertise within the Hub. They include work on reinforcement learning, causal inference, diffusion models, and the theoretical analysis of machine learning systems, alongside several high-profile collaborative projects.
Hub Director Michael Bronstein and colleagues contributed an exceptional 17 papers.
Other contributors include Ran Levi, whose collaborative project paper develops new topological neural network models for learning from complex, higher-order relational data. Alessandro Abate also co-authored an accepted paper with L. Carvalho Melo and Yarin Gal, on challenges in reinforcement learning for large language model reasoning.
The Erlangen Hub is further represented in foundational work on causality and learning, with Marta Kwiatkowska co-authoring an accepted paper on causal imitation learning in the presence of hidden confounders, while Patrick Rebeschini co-authored a paper offering new theoretical insights into diffusion models, an increasingly important class of generative models in modern AI.
In other conference news, Hub PDRAs Francesco Fabiano and Thom Badings presented the paper “Best-Effort Policies for Robust Markov Decision Processes”, a collaboration with Co-Investigators Alessandro Abate and Giuseppe De Giacomo, at the AAAI 2026 conference in Singapore. Thom also received an honourable mention in the AAAI and ACM SIGAI Doctoral Dissertation Award and delivered his own talk at AAAI 2026. Hub Co-I Gesine Reinert has contributed two papers this year to the AIStats conference, taking place later this year in Morocco.
Taken together, these achievements highlight the Erlangen Hub’s growing international profile and its impact across the most active and influential areas of artificial intelligence research. They reflect both individual research excellence and a strong culture of collaboration and high-quality scholarship within the Hub.