Balazs Kulcsar — accepted AI-conference papers

2026

Beyond Simple Graphs: Neural Multi-Objective Routing on Multigraphs

Filip Rydin, Attila Lischka, Jiaming Wu, Morteza Haghir Chehreghani, Balazs Kulcsar

ICLR 2026poster

Learning-based methods for routing have gained significant attention in recent years, both in single-objective and multi-objective contexts. Yet, existing methods are unsuitable for routing on multigraphs, which feature multiple edges with distinct attributes between node pairs, despite their strong…

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2022

On the Interpretability of Regularisation for Neural Networks Through Model Gradient Similarity

Vincent Szolnoky, Viktor Andersson, Balazs Kulcsar, Rebecka Jörnsten

NeurIPS 2022accept

Most complex machine learning and modelling techniques are prone to over-fitting and may subsequently generalise poorly to future data. Artificial neural networks are no different in this regard and, despite having a level of implicit regularisation when trained with gradient descent, often require…

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