CausalBench Challenge

CausalBench is a benchmark platform designed to advance causal learning research by providing standardized datasets, algorithms, and evaluation metrics. Current research focuses on evaluating the causal reasoning capabilities of large language models (LLMs) across various tasks, comparing their performance to traditional causal inference methods, and developing techniques for causally-aware representation learning in complex systems like multi-agent interactions and gene networks. The platform's impact lies in fostering more rigorous and reproducible research in causal inference, ultimately leading to improved methods for understanding and predicting causal relationships in diverse scientific domains and practical applications such as drug discovery.

Papers

September 12, 2024

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
Machine Learning Causal Relationship Causal Direction Causal Analysis Causal Learning Benchmark Framework CausalBench Challenge

April 9, 2024

CausalBench: A Comprehensive Benchmark for Causal Learning Capability of LLMs
Yu Zhou, Xingyu Wu, Beicheng Huang, Jibin Wu, Liang Feng, Kay Chen Tan
Comprehensive Benchmark Causal Learning Causal Network Causal Interpretation Causality Analysis CausalBench Challenge

December 7, 2023

Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations
Yuejiang Liu, Ahmad Rahimi, Po-Chien Luan, Frano Rajič, Alexandre Alahi
Metric Learning Causal Representation Learning Sim to Real Transfer Interaction Representation CausalBench Challenge

August 29, 2023

The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data
Mathieu Chevalley, Jacob Sackett-Sanders, Yusuf Roohani, Pascal Notin, Artemy Bakulin, Dariusz Brzezinski, Kaiwen Deng, Yuanfang Guan, Justin Hong, Michael Ibrahim, Wojciech Kotlowski, Marcin Kowiel, Panagiotis Misiakos, Achille Nazaret, Markus Püschel, Chris Wendler, Arash Mehrjou, Patrick Schwab
Gene Regulatory Neural Network CausalBench Challenge

October 31, 2022

CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data
Mathieu Chevalley, Yusuf Roohani, Arash Mehrjou, Jure Leskovec, Patrick Schwab
Causal Inference Large Scale Benchmark Network Inference CausalBench Challenge

CausalBench Challenge

Papers

Introducing CausalBench: A Flexible Benchmark Framework for Causal Analysis and Machine Learning

CausalBench: A Comprehensive Benchmark for Causal Learning Capability of LLMs

Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations

The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data

CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data