Papers

CausalBench is also an academic work, and every now and then, we push the boundaries of Collaborative Benchmarking with Causality, and lower the bar of entry into the domain. Through this endeavor, we write, publish, and present works. Below is an active list of our work:

Conference Appearances

• KDD'25, Hands-on Tutorial: "CausalBench: Causal Learning Research Streamlined". Paper, Tutorial page
• CIKM'24, Best Demo-Paper Award: "Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning". Paper

Reports and Papers

• CausalBench: A Unifying Framework for Benchmarking Causal Learning Models. Link