IJCAI-ECAI 2026 tutorial / workshop round-up part 1

In this summary article, organisers of a tutorial and a workshop at IJCAI-ECAI 2026 pick their key takeaways from their respective sessions. This tutorial was a practical, hands-on tutorial on the theory and methods for handling missing data in tabular and imaging settings, from statistical baselines to autoencoders and generative adversarial networks. The missingness mechanism is more important than the choice of imputation method. MCAR, MAR, and MNAR settings call for different treatment, and MNAR, the most challenging mechanism, is the one that most methods do not handle well. Deep generative imputation is not always better.