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cs.AI2024
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding
Henri Arno, Paloma Rabaey, Thomas Demeester
One of the central goals of causal machine learning is the accurate estimation of heterogeneous treatment effects from observational data. In recent years, meta-learning has emerge…
cs.CE2024
From Numbers to Words: Multi-Modal Bankruptcy Prediction Using the ECL Dataset
Henri Arno, Klaas Mulier, Joke Baeck +1
In this paper, we present ECL, a novel multi-modal dataset containing the textual and numerical data from corporate 10K filings and associated binary bankruptcy labels. Furthermore…