Home › Datasets › task › Causal Discovery

Causal Discovery datasets

archive 2025-07-28

5 datasets carry the task tag "Causal Discovery" (the task itself: Causal Discovery), ordered by the archive's paper count. Page 1 of 1: 5 shown of 5. Facet routes are this site's own (the archive records the tag string, not a page).

The archive holds 12,214 dataset rows; 12,172 are listed. 6 are withheld from every listing and count here as vandalised before snapshot (6 with contact-centre spam in the title, 0 with a spam description on a row that has no homepage, no paper and no papers counted; none with more than 1 paper, 0 with a benchmark), listed in withheld.json; 1 listed row carries a vandalised description, withheld on its page. This gate never withholds a row with a homepage or a paper that resolves, and a clean description; the content rules below withhold a row whose name is spam whatever else it carries. The gate is a phrase list: these are the rows it caught, not a claim that the rest is clean. Before that gate, the site's content rules withhold 36 more rows (invite-code, gambling, travel-booking, contact-centre and similar spam in the name or on a row with nothing real behind it); they have no page and are listed in withheld.json.

Filter 51 task tags shown of 3,717, by dataset count; the full filter by modality, task and language is on /datasets

Causal Discovery datasets 1–5 of 5

CausalBench is a comprehensive benchmark suite for evaluating network inference methods on large-scale perturbational single-cell gene expression data.
4 papers · 0 benchmarks
BCOPA-CE (A Balanced COPA Test Set with cause-effect as alternatives)
We provide the BCOPA-CE test set, which has balanced token distribution in the correct and wrong alternatives and increases the difficulty of being aware of cause and effect.
3 papers · 0 benchmarks
The raw data are obtained from an industrial plant for ultra-processed food production.
2 papers · 0 benchmarks
TimeGraph (TimeGraph: Synthetic Benchmark Datasets for Robust Time-Series Causal Discovery)
TimeGraph is a comprehensive suite of synthetic datasets designed to benchmark causal discovery algorithms on time-series data.
1 paper · 0 benchmarks

Paper counts and descriptions are the archive's, frozen 2025-07-28; no citation counts, no stars, no trending. Sorting by "most cited" or "newest" was a live-site feature the archive does not carry.