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Interventions
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation
The practical utility of causality in decision-making is widely recognized, with causal discovery and inference being inherently …
Chris Chinenye Emezue
,
Alexandre Drouin
,
Tristan Deleu
,
Stefan Bauer
,
Yoshua Bengio
Workshop on Structured Probabilistic Inference & Generative Modeling (ICML), 2023.
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Differentiable Causal Discovery from Interventional Data
Learning a causal directed acyclic graph from data is a challenging task that involves solving a combinatorial problem for which the …
Philippe Brouillard
,
Sébastien Lachapelle
,
Alexandre Lacoste
,
Simon Lacoste-Julien
,
Alexandre Drouin
Conference on Neural Information Processing Systems (NeurIPS), 2020.
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Gradient-Based Neural DAG Learning with Interventions
Decision making based on statistical association alone can be a dangerous en- deavor due to non-causal associations. Ideally, one would …
Philippe Brouillard
,
Alexandre Drouin
,
Sébastien Lachapelle
,
Alexandre Lacoste
,
Simon Lacoste-Julien
Workshop at the International Conference on Learning Representations (ICLR), 2020.
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