# Equivalent Causal Models

arXiv: https://arxiv.org/abs/2012.05603 · HTML: https://mlsanity.com/paper/2012.05603/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Dec 2020.

## Built on by (most cited first, 4 of 4)

- [Coarsening Causal DAG Models](https://mlsanity.com/paper/2601.10531/) (2026)
- [The Relativity of Causal Knowledge](https://mlsanity.com/paper/2503.11718/) (2025)
- [Temporal Causal Reasoning with (Non-Recursive) Structural Equation Models](https://mlsanity.com/paper/2501.10190/) (2025)
- [Beyond the Black Box: Identifiable Interpretation and Control in Generative Models via Causal Minimality](https://mlsanity.com/paper/2512.10720/) (2025)

## Abstract (arXiv)

The aim of this paper is to offer the first systematic exploration and definition of equivalent causal models in the context where both models are not made up of the same variables. The idea is that two models are equivalent when they agree on all "essential" causal information that can be expressed using their common variables. I do so by focussing on the two main features of causal models, namely their structural relations and their functional relations. In particular, I define several relations of causal ancestry and several relations of causal sufficiency, and require that the most general of these relations are preserved across equivalent models.