CausalMMM: Learning Causal Structure for Marketing Mix Modeling

24 June 2024

Papers citing "CausalMMM: Learning Causal Structure for Marketing Mix Modeling"

8 / 8 papers shown

Title
LOCAL: Learning with Orientation Matrix to Infer Causal Structure from Time Series Data Yue Cheng Jiajun Zhang Weiwei Xing Xiaoyu Guo Yue Cheng Witold Pedrycz CML 84 0 0 25 Oct 2024
Granger Causality: A Review and Recent Advances Ali Shojaie E. Fox CML AI4TS 63 269 0 05 May 2021
D'ya like DAGs? A Survey on Structure Learning and Causal Discovery M. Vowels Necati Cihan Camgöz Richard Bowden CML 107 300 0 03 Mar 2021
Causal Inference for Time series Analysis: Problems, Methods and Evaluation Raha Moraffah Paras Sheth Mansooreh Karami Anchit Bhattacharya Qianru Wang Anique Tahir A. Raglin Huan Liu CML AI4TS 91 107 0 11 Feb 2021
Inductive Granger Causal Modeling for Multivariate Time Series Yunfei Chu Xiaowei Wang Jianxin Ma Kunyang Jia Jingren Zhou Hongxia Yang CML AI4TS 33 11 0 10 Feb 2021
Hierarchical Marketing Mix Models with Sign Constraints Hao Chen M. Zhang Lanshan Han Alvin Lim 41 10 0 28 Aug 2020
High-recall causal discovery for autocorrelated time series with latent confounders Andreas Gerhardus J. Runge CML AI4TS 48 102 0 03 Jul 2020
Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causality Saurabh Khanna Vincent Y. F. Tan AI4TS 47 72 0 22 Nov 2019