Estimating Visual Attribute Effects in Advertising from Observational Data: A Deepfake-Informed Double Machine Learning Approach
Fuente:
arXiv
Saved in:
| Main Authors: | Liu, Yizhi, Padmanabhan, Balaji, Viswanathan, Siva |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
A Double Machine Learning Approach to Combining Experimental and Observational Data
by: Parikh, Harsh, et al.
Published: (2023)
by: Parikh, Harsh, et al.
Published: (2023)
From Deception to Perception: The Surprising Benefits of Deepfakes for Detecting, Measuring, and Mitigating Bias
by: Liu, Yizhi, et al.
Published: (2025)
by: Liu, Yizhi, et al.
Published: (2025)
What Exactly is a Deepfake?
by: Liu, Yizhi, et al.
Published: (2025)
by: Liu, Yizhi, et al.
Published: (2025)
Learning from Double Positive and Unlabeled Data for Potential-Customer Identification
by: Kato, Masahiro, et al.
Published: (2025)
by: Kato, Masahiro, et al.
Published: (2025)
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data
by: Klaassen, Sven, et al.
Published: (2024)
by: Klaassen, Sven, et al.
Published: (2024)
Sufficient conditions for a Heuristic Rating Estimation Method application
by: Szybowski, Jacek, et al.
Published: (2026)
by: Szybowski, Jacek, et al.
Published: (2026)
Global Neural Networks and The Data Scaling Effect in Financial Time Series Forecasting
by: Liu, Chen, et al.
Published: (2023)
by: Liu, Chen, et al.
Published: (2023)
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators
by: Huang, Yiyan, et al.
Published: (2024)
by: Huang, Yiyan, et al.
Published: (2024)
The Persistent Effects of Peru's Mining MITA: Double Machine Learning Approach
by: Karakas, Alper Deniz
Published: (2025)
by: Karakas, Alper Deniz
Published: (2025)
A Deep Learning Representation of Spatial Interaction Model for Resilient Spatial Planning of Community Business Clusters
by: Hao, Haiyan, et al.
Published: (2024)
by: Hao, Haiyan, et al.
Published: (2024)
Management Decisions in Manufacturing using Causal Machine Learning -- To Rework, or not to Rework?
by: Schwarz, Philipp, et al.
Published: (2024)
by: Schwarz, Philipp, et al.
Published: (2024)
Forecasting Labor Demand: Predicting JOLT Job Openings using Deep Learning Model
by: Kim, Kyungsu
Published: (2025)
by: Kim, Kyungsu
Published: (2025)
Certificates without Electrons? Theory and Evidence on Impacts from AI-Driven Power Demand
by: Golden, Dana, et al.
Published: (2026)
by: Golden, Dana, et al.
Published: (2026)
AI Assisted Economics Measurement From Survey: Evidence from Public Employee Pension Choice
by: Wang, Tiancheng, et al.
Published: (2026)
by: Wang, Tiancheng, et al.
Published: (2026)
Can AI Master Econometrics? Evidence from Econometrics AI Agent on Expert-Level Tasks
by: Chen, Qiang, et al.
Published: (2025)
by: Chen, Qiang, et al.
Published: (2025)
Neural Network Modeling for Forecasting Tourism Demand in Stopića Cave: A Serbian Cave Tourism Study
by: Bajić, Buda, et al.
Published: (2024)
by: Bajić, Buda, et al.
Published: (2024)
Estimating Causal Effects with Double Machine Learning -- A Method Evaluation
by: Fuhr, Jonathan, et al.
Published: (2024)
by: Fuhr, Jonathan, et al.
Published: (2024)
Deep Learning Enhanced Multivariate GARCH
by: Wang, Haoyuan, et al.
Published: (2025)
by: Wang, Haoyuan, et al.
Published: (2025)
xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R
by: Polselli, Annalivia
Published: (2025)
by: Polselli, Annalivia
Published: (2025)
Bayesian Double Machine Learning for Causal Inference
by: DiTraglia, Francis J., et al.
Published: (2025)
by: DiTraglia, Francis J., et al.
Published: (2025)
Can large language models assist choice modelling? Insights into prompting strategies and current models capabilities
by: Sfeir, Georges, et al.
Published: (2025)
by: Sfeir, Georges, et al.
Published: (2025)
Large Language Models: An Applied Econometric Framework
by: Ludwig, Jens, et al.
Published: (2024)
by: Ludwig, Jens, et al.
Published: (2024)
From Model Choice to Model Belief: Establishing a New Measure for LLM-Based Research
by: Sun, Hongshen, et al.
Published: (2025)
by: Sun, Hongshen, et al.
Published: (2025)
Evaluating the Accuracy of Chatbots in Financial Literature
by: Erdem, Orhan, et al.
Published: (2024)
by: Erdem, Orhan, et al.
Published: (2024)
Structural Estimation of Markov Decision Processes in High-Dimensional State Space with Finite-Time Guarantees
by: Zeng, Siliang, et al.
Published: (2022)
by: Zeng, Siliang, et al.
Published: (2022)
An Empirical Risk Minimization Approach for Offline Inverse RL and Dynamic Discrete Choice Model
by: Kang, Enoch H., et al.
Published: (2025)
by: Kang, Enoch H., et al.
Published: (2025)
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement Learning
by: Dong, Stella C.
Published: (2025)
by: Dong, Stella C.
Published: (2025)
Double Machine Learning for Time Series
by: Ciganovic, Milos, et al.
Published: (2026)
by: Ciganovic, Milos, et al.
Published: (2026)
A primer on optimal transport for causal inference with observational data
by: Gunsilius, Florian F
Published: (2025)
by: Gunsilius, Florian F
Published: (2025)
Causal EpiNets: Precision-corrected Bounds on Individual Treatment Effects using Epistemic Neural Networks
by: Patil, Gandharv, et al.
Published: (2026)
by: Patil, Gandharv, et al.
Published: (2026)
Scaling Causal Mediation for Complex Systems: A Framework for Root Cause Analysis
by: Casadei, Alessandro, et al.
Published: (2025)
by: Casadei, Alessandro, et al.
Published: (2025)
Neighborhood Stability in Double/Debiased Machine Learning with Dependent Data
by: Cao, Jianfei, et al.
Published: (2025)
by: Cao, Jianfei, et al.
Published: (2025)
Non-linear Phillips Curve for India: Evidence from Explainable Machine Learning
by: Sengupta, Shovon, et al.
Published: (2025)
by: Sengupta, Shovon, et al.
Published: (2025)
Simulation-Based Benchmarking of Reinforcement Learning Agents for Personalized Retail Promotions
by: Xia, Yu, et al.
Published: (2024)
by: Xia, Yu, et al.
Published: (2024)
Learning Causal Representations from General Environments: Identifiability and Intrinsic Ambiguity
by: Jin, Jikai, et al.
Published: (2023)
by: Jin, Jikai, et al.
Published: (2023)
Double Machine Learning for Static Panel Models with Fixed Effects
by: Clarke, Paul S., et al.
Published: (2023)
by: Clarke, Paul S., et al.
Published: (2023)
Estimating Continuous Treatment Effects in Panel Data using Machine Learning with a Climate Application
by: Klosin, Sylvia, et al.
Published: (2022)
by: Klosin, Sylvia, et al.
Published: (2022)
Econometric vs. Causal Structure-Learning for Time-Series Policy Decisions: Evidence from the UK COVID-19 Policies
by: Petrungaro, Bruno, et al.
Published: (2026)
by: Petrungaro, Bruno, et al.
Published: (2026)
Adaptive Experimental Design for Policy Learning
by: Kato, Masahiro, et al.
Published: (2024)
by: Kato, Masahiro, et al.
Published: (2024)
A Network Simulation of OTC Markets with Multiple Agents
by: Wilkinson, James T., et al.
Published: (2024)
by: Wilkinson, James T., et al.
Published: (2024)
Similar Items
-
A Double Machine Learning Approach to Combining Experimental and Observational Data
by: Parikh, Harsh, et al.
Published: (2023) -
From Deception to Perception: The Surprising Benefits of Deepfakes for Detecting, Measuring, and Mitigating Bias
by: Liu, Yizhi, et al.
Published: (2025) -
What Exactly is a Deepfake?
by: Liu, Yizhi, et al.
Published: (2025) -
Learning from Double Positive and Unlabeled Data for Potential-Customer Identification
by: Kato, Masahiro, et al.
Published: (2025) -
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data
by: Klaassen, Sven, et al.
Published: (2024)