Cover Image

CausalMMM: Learning Causal Structure for Marketing Mix Modeling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gong, Chang, Yao, Di, Zhang, Lei, Chen, Sheng, Li, Wenbin, Su, Yueyang, Bi, Jingping
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GTool: Graph Enhanced Tool Planning with Large Language Model
by: Chen, Wenjie, et al.
Published: (2025)

Effective and Efficient Representation Learning for Flight Trajectories
by: Liu, Shuo, et al.
Published: (2024)

DeepCausalMMM: A Deep Learning Framework for Marketing Mix Modeling with Causal Structure Learning
by: Tirumala, Aditya Puttaparthi
Published: (2025)

Individual Causal Inference with Structural Causal Model
by: Chang, Daniel T.
Published: (2025)

PORCA: Root Cause Analysis with Partially Observed Data
by: Gong, Chang, et al.
Published: (2024)

Distribution-consistency Structural Causal Models
by: Gong, Heyang, et al.
Published: (2024)

CausalTAD: Causal Implicit Generative Model for Debiased Online Trajectory Anomaly Detection
by: Li, Wenbin, et al.
Published: (2024)

AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
by: Liu, Shuo, et al.
Published: (2024)

Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)

Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning
by: Ling, Zhaolong, et al.
Published: (2021)

MMM: Generative Masked Motion Model
by: Pinyoanuntapong, Ekkasit, et al.
Published: (2023)

Causality-aligned Prompt Learning via Diffusion-based Counterfactual Generation
by: Li, Xinshu, et al.
Published: (2025)

Causal-LLaVA: Causal Disentanglement for Mitigating Hallucination in Multimodal Large Language Models
by: Hu, Xinmiao, et al.
Published: (2025)

Traj-MLLM: Can Multimodal Large Language Models Reform Trajectory Data Mining?
by: Liu, Shuo, et al.
Published: (2025)

SOM: Structured Opponent Modeling for LLM-based Agents via Structural Causal Model
by: Cao, Shiyue, et al.
Published: (2026)

Fairness-Aware Streaming Feature Selection with Causal Graphs
by: Zhang, Leizhen, et al.
Published: (2024)

Temporal Latent Variable Structural Causal Model for Causal Discovery under External Interferences
by: Cai, Ruichu, et al.
Published: (2025)

Efficient Transfer Learning via Causal Bounds
by: Gong, Xueping, et al.
Published: (2023)

Causal computations in Semi Markovian Structural Causal Models using divide and conquer
by: Bjøru, Anna Rodum, et al.
Published: (2025)

A Causal Information-Flow Framework for Unbiased Learning-to-Rank
by: Gong, Haoming, et al.
Published: (2026)

Causality Without Causal Models
by: Halpern, Joseph Y., et al.
Published: (2025)

Caracal: Causal Architecture via Spectral Mixing
by: Gan, Bingzheng, et al.
Published: (2026)

Causal Structure and Representation Learning with Biomedical Applications
by: Uhler, Caroline, et al.
Published: (2025)

DODO: Causal Structure Learning with Budgeted Interventions
by: Gregorini, Matteo, et al.
Published: (2025)

Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
by: Bu, Yunhan, et al.
Published: (2026)

Test-Time Learning of Causal Structure from Interventional Data
by: Chen, Wei, et al.
Published: (2026)

How to Marginalize in Causal Structure Learning?
by: Zhao, William, et al.
Published: (2025)

CausalEval: Towards Better Causal Reasoning in Language Models
by: Yu, Longxuan, et al.
Published: (2024)

CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health state
by: Li, Xiang, et al.
Published: (2024)

Causally Aligned Curriculum Learning
by: Li, Mingxuan, et al.
Published: (2025)

Humanoid-inspired Causal Representation Learning for Domain Generalization
by: Tao, Ze, et al.
Published: (2025)

Biological Regulatory Network Inference through Circular Causal Structure Learning
by: Jiang, Hongyang, et al.
Published: (2025)

Learning by Doing: An Online Causal Reinforcement Learning Framework with Causal-Aware Policy
by: Cai, Ruichu, et al.
Published: (2024)

Causal Discovery as Dialectical Aggregation: A Quantitative Argumentation Framework
by: Wei, Sheng, et al.
Published: (2026)

Hybrid Causal Identification and Causal Mechanism Clustering
by: Liu, Saixiong, et al.
Published: (2025)

Local Causal Structure Learning in the Presence of Latent Variables
by: Xie, Feng, et al.
Published: (2024)

Learning Structural Causal Models from Ordering: Identifiable Flow Models
by: Le, Minh Khoa, et al.
Published: (2024)

Causal Temporal Regime Structure Learning
by: Rahmani, Abdellah, et al.
Published: (2023)

Unbiased Evaluation of Large Language Models from a Causal Perspective
by: Chen, Meilin, et al.
Published: (2025)

Deep Causal Learning to Explain and Quantify The Geo-Tension's Impact on Natural Gas Market
by: Peter, Philipp Kai, et al.
Published: (2024)