Search Results for author: Scott Sussex

Found 6 papers, 3 papers with code

Standardizing Structural Causal Models

no code implementations17 Jun 2024 Weronika Ormaniec, Scott Sussex, Lars Lorch, Bernhard Schölkopf, Andreas Krause

Moreover, contrary to the post-hoc standardization of data generated by standard SCMs, we prove that linear iSCMs are less identifiable from prior knowledge on the weights and do not collapse to deterministic relationships in large systems, which may make iSCMs a useful model in causal inference beyond the benchmarking problem studied here.

Benchmarking Causal Inference

Model-based Causal Bayesian Optimization

no code implementations31 Jul 2023 Scott Sussex, Pier Giuseppe Sessa, Anastasiia Makarova, Andreas Krause

We formalize this generalization of CBO as Adversarial Causal Bayesian Optimization (ACBO) and introduce the first algorithm for ACBO with bounded regret: Causal Bayesian Optimization with Multiplicative Weights (CBO-MW).

Bayesian Optimization counterfactual +1

Model-based Causal Bayesian Optimization

1 code implementation18 Nov 2022 Scott Sussex, Anastasiia Makarova, Andreas Krause

How should we intervene on an unknown structural equation model to maximize a downstream variable of interest?

Bayesian Optimization model

Amortized Inference for Causal Structure Learning

1 code implementation25 May 2022 Lars Lorch, Scott Sussex, Jonas Rothfuss, Andreas Krause, Bernhard Schölkopf

Rather than searching over structures, we train a variational inference model to directly predict the causal structure from observational or interventional data.

Causal Discovery Inductive Bias +1

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