Smoke and Mirrors in Causal Downstream Tasks

no code implementations • 27 May 2024 • Riccardo Cadei, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, Francesco Locatello

Machine Learning and AI have the potential to transform data-driven scientific discovery, enabling accurate predictions for several scientific phenomena.

Towards Robust and Adaptive Motion Forecasting: A Causal Representation Perspective

2 code implementations • CVPR 2022 • Yuejiang Liu, Riccardo Cadei, Jonas Schweizer, Sherwin Bahmani, Alexandre Alahi

Learning behavioral patterns from observational data has been a de-facto approach to motion forecasting.

Motion Forecasting Out-of-Distribution Generalization +1

Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects

no code implementations • 18 Sep 2020 • Falco J. Bargagli-Stoffi, Riccardo Cadei, Kwonsang Lee, Francesca Dominici

Estimation of subgroup-specific causal effects is performed via a two-stage approach for which we provide theoretical guarantees.

Causal Inference Epidemiology