causaLens researchers Andrew Lawrence, Marcus Kaiser, Rui Sampaio, and Maksim Sipos introduce a novel framework for evaluating and benchmarking causal discovery methods for time-series data. The paper — which also evaluates prominent causal discovery algorithms, and sets out how the framework can supports researchers and data science practitioners — was presented at leading AI conference NeurIPS.
