Yau M., Karalias N., Lu E., Xu J., Jegelka S. (2024). Are Graph Neural Networks Optimal Approximation Algorithms? NeurIPS 2024 Spotlight. (arxiv)

Karalias N., Robinson J., Loukas A., Jegelka S. (2022). Neural Set Function Extensions: Learning with Discrete Functions in High Dimensions. NeurIPS 2022. (arxiv, proceedings, blogpost, video presentation)

Karalias N., & Loukas A. (2020). Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs. NeurIPS 2020 Oral (arxiv, code, blogpost, short presentation, podcast, bibtex)

Bouritsas G., Loukas A., Karalias N., Bronstein M. (2021). Partition and Code: learning how to compress graphs. Advances in Neural Information Processing Systems, 34. (arxiv, code, slides, bibtex)