LFhase / CIGA

[NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs

Date Created 2022-10-06 (2 years ago)

Commits 30 (last one about a year ago)

Stargazers 104 (0 this week)

Watchers 4 (0 this week)

Forks 11

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RepositoryStats indexes 595,856 repositories, of these LFhase/CIGA is ranked #286,904 (52nd percentile) for total stargazers, and #377,401 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #53,277/119,431.

LFhase/CIGA is also tagged with popular topics, for these it's ranked: graph-neural-networks (#273/592), drug-discovery (#61/120), causal-inference (#55/114)

Other Information

Homepage URL: https://arxiv.org/abs/2202.05441

All Topics

drug-discovery causal-inference distribution-shift invariant-learning graph-neural-networks graph-representation-learning causal-representation-learning out-of-distribution-generalization

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30 commits on the default branch (main) since jan '22

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updated: 2024-12-20 @ 06:52am, id: 546551158 / R_kgDOIJO1dg