ML Anthology

eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-Stationary Data (Student Abstract)

Muhammad Hasan Ferdous, Uzma Hasan, Md. Osman Gani
AAAI 2023 pp. 16208-16209
doi:10.1609/AAAI.V37I13.26964 /aaai/2023/ferdous2023aaai-ecdans/
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Cite

Text

Ferdous et al. "eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-Stationary Data (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023. doi:10.1609/AAAI.V37I13.26964

Markdown

[Ferdous et al. "eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-Stationary Data (Student Abstract)." AAAI Conference on Artificial Intelligence, 2023.](https://mlanthology.org/aaai/2023/ferdous2023aaai-ecdans/) doi:10.1609/AAAI.V37I13.26964

BibTeX

@inproceedings{ferdous2023aaai-ecdans,
  title     = {{eCDANs: Efficient Temporal Causal Discovery from Autocorrelated and Non-Stationary Data (Student Abstract)}},
  author    = {Ferdous, Muhammad Hasan and Hasan, Uzma and Gani, Md. Osman},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2023},
  pages     = {16208-16209},
  doi       = {10.1609/AAAI.V37I13.26964},
  url       = {https://mlanthology.org/aaai/2023/ferdous2023aaai-ecdans/}
}