Abstract
In this work, we deepen on the use of normalizing flows for causal reasoning. Specifically, we first leverage recent results on non-linear ICA to show that causal models are identifiable from observational data given a causal ordering, and thus can be recovered using autoregressive normalizing flows (NFs). Second, we analyze different design and learning choices for causal normalizing flows to capture the underlying causal data-generating process. Third, we describe how to implement the do-operator in causal NFs, and thus, how to answer interventional and counterfactual questions. Finally, in our experiments, we validate our design and training choices through a comprehensive ablation study; compare causal NFs to other approaches for approximating causal models; and empirically demonstrate that causal NFs can be used to address real-world problems—where the presence of mixed discrete-continuous data and partial knowledge on the causal graph is the norm. The code for this work can be found at https://github.com/psanch21/causal-flows.
Original language | English |
---|---|
Title of host publication | Advances in Neural Information Processing Systems 36 (NeurIPS 2023) |
Editors | Alice Oh, Tristan Naumann, Amir Globerson, Kate Saenko, Moritz Hardt, Sergey Levine |
Publisher | Neural Information Processing Systems Foundation (NeurIPS) |
Pages | 1-32 |
Number of pages | 32 |
ISBN (Electronic) | 9781713899921 |
Publication status | Published - 16 Dec 2023 |
Event | Thirty-Seventh Conference on Neural Information Processing Systems - New Orleans Ernest N. Morial Convention Center, New Orleans, United States Duration: 10 Dec 2023 → 16 Dec 2023 Conference number: 37 https://neurips.cc/Conferences/2023 |
Publication series
Name | Advances in Neural Information Processing Systems |
---|---|
Publisher | NeurIPS |
ISSN (Print) | 1049-5258 |
Conference
Conference | Thirty-Seventh Conference on Neural Information Processing Systems |
---|---|
Abbreviated title | NeurIPS 2023 |
Country/Territory | United States |
City | New Orleans |
Period | 10/12/23 → 16/12/23 |
Internet address |
Keywords / Materials (for Non-textual outputs)
- machine learning
- artificial intelligence
- methodology