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stat.ML2024
Learning Structural Causal Models through Deep Generative Models: Methods, Guarantees, and Challenges
Audrey Poinsot, Alessandro Leite, Nicolas Chesneau +2
This paper provides a comprehensive review of deep structural causal models (DSCMs), particularly focusing on their ability to answer counterfactual queries using observational dat…
stat.ML2024★ 1 cited
Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
Edgar Jaber, Vincent Blot, Nicolas Brunel +6
Gaussian processes (GPs) are a Bayesian machine learning approach widely used to construct surrogate models for the uncertainty quantification of computer simulation codes in indus…