Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning.
Ahmet Kapkiç|Pratanu Mandal|Shu Wan|Paras Sheth|Abhinav Gorantla|Yoonhyuk Choi|Huan Liu|K. Selçuk Candan
| Anthology ID: | DBLP:conf/cikm/KapkicM0SGC0C24 |
|---|---|
| Volume: | Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024 |
| Year: | 2024 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 5220-5224 |
| URL: | https://doi.org/10.1145/3627673.3679218 |
| DOI: | https://doi.org/10.1145/3627673.3679218 |
| DBLP: | conf/cikm/KapkicM0SGC0C24 |
| BibTeX: |
@inproceedings{kapkic-2024-introducing,
author = {Ahmet Kapki\c{c} and
Pratanu Mandal and
Shu Wan and
Paras Sheth and
Abhinav Gorantla and
Yoonhyuk Choi and
Huan Liu and
K. Sel\c{c}uk Candan},
editor = {Edoardo Serra and
Francesca Spezzano},
title = {{Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning}},
booktitle = {{Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, CIKM 2024, Boise, ID, USA, October 21-25, 2024}},
pages = {5220--5224},
publisher = {ACM},
year = {2024},
url = {https://doi.org/10.1145/3627673.3679218},
doi = {https://doi.org/10.1145/3627673.3679218}
}