2 papers
cs.AI2026
The Digital Twin Counterfactual Framework: A Validation Architecture for Simulated Potential Outcomes
Olav Laudy
The fundamental problem of causal inference - that the counterfactual outcome for any individual is never observed - has shaped the entire methodology of the field. Every existing…
stat.ML2016
Churn analysis using deep convolutional neural networks and autoencoders
Artit Wangperawong, Cyrille Brun, Olav Laudy +1
Customer temporal behavioral data was represented as images in order to perform churn prediction by leveraging deep learning architectures prominent in image classification. Superv…