Saved in:
| Main Authors: | Murakami, Yuki, Hattori, Takumi, Kubota, Kohsuke |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.09814 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Causal Inference under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects
by: Kubota, Kohsuke, et al.
Published: (2025)
by: Kubota, Kohsuke, et al.
Published: (2025)
Off-Policy Evaluation and Learning for Survival Outcomes under Censoring
by: Kubota, Kohsuke, et al.
Published: (2026)
by: Kubota, Kohsuke, et al.
Published: (2026)
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks
by: Cui, Ziqiang, et al.
Published: (2024)
by: Cui, Ziqiang, et al.
Published: (2024)
Conformal Prediction for Causal Effects of Continuous Treatments
by: Schröder, Maresa, et al.
Published: (2024)
by: Schröder, Maresa, et al.
Published: (2024)
Compositional Models for Estimating Causal Effects
by: Pruthi, Purva, et al.
Published: (2024)
by: Pruthi, Purva, et al.
Published: (2024)
Copula-Based Endogeneity Correction for Doubly Robust Estimation of Treatment Effect
by: Shikalgar, Sahil, et al.
Published: (2026)
by: Shikalgar, Sahil, et al.
Published: (2026)
Measure-Theoretic Anti-Causal Representation Learning
by: Behnam, Arman, et al.
Published: (2025)
by: Behnam, Arman, et al.
Published: (2025)
The Estimation of Continual Causal Effect for Dataset Shifting Streams
by: Chen, Baining, et al.
Published: (2025)
by: Chen, Baining, et al.
Published: (2025)
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation
by: Reddy, Abbavaram Gowtham, et al.
Published: (2022)
by: Reddy, Abbavaram Gowtham, et al.
Published: (2022)
Moments of Causal Effects
by: Kawakami, Yuta, et al.
Published: (2025)
by: Kawakami, Yuta, et al.
Published: (2025)
Defining Expertise: Applications to Treatment Effect Estimation
by: Hüyük, Alihan, et al.
Published: (2024)
by: Hüyük, Alihan, et al.
Published: (2024)
Data-Driven Estimation of Heterogeneous Treatment Effects
by: Tran, Christopher, et al.
Published: (2023)
by: Tran, Christopher, et al.
Published: (2023)
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
by: Mahajan, Divyat, et al.
Published: (2022)
by: Mahajan, Divyat, et al.
Published: (2022)
On Efficient Adjustment for Micro Causal Effects in Summary Causal Graphs
by: Belciug, Isabela, et al.
Published: (2025)
by: Belciug, Isabela, et al.
Published: (2025)
Constrained Identifiability of Causal Effects
by: Chen, Yizuo, et al.
Published: (2024)
by: Chen, Yizuo, et al.
Published: (2024)
Bounding Causal Effects with Leaky Instruments
by: Watson, David S., et al.
Published: (2024)
by: Watson, David S., et al.
Published: (2024)
Text Rationalization for Robust Causal Effect Estimation
by: Zhang, Lijinghua, et al.
Published: (2025)
by: Zhang, Lijinghua, et al.
Published: (2025)
Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference
by: Cai, Hengrui, et al.
Published: (2024)
by: Cai, Hengrui, et al.
Published: (2024)
Towards Interpretable Deep Generative Models via Causal Representation Learning
by: Moran, Gemma E., et al.
Published: (2025)
by: Moran, Gemma E., et al.
Published: (2025)
Sanity Checking Causal Representation Learning on a Simple Real-World System
by: Gamella, Juan L., et al.
Published: (2025)
by: Gamella, Juan L., et al.
Published: (2025)
Black Box Causal Inference: Effect Estimation via Meta Prediction
by: Bynum, Lucius E. J., et al.
Published: (2025)
by: Bynum, Lucius E. J., et al.
Published: (2025)
Towards Learning and Explaining Indirect Causal Effects in Neural Networks
by: Reddy, Abbavaram Gowtham, et al.
Published: (2023)
by: Reddy, Abbavaram Gowtham, et al.
Published: (2023)
Identifying Macro Causal Effects in C-DMGs over DMGs
by: Ferreira, Simon, et al.
Published: (2025)
by: Ferreira, Simon, et al.
Published: (2025)
Robust Weighted Triangulation of Causal Effects Under Model Uncertainty
by: Bhattacharya, Rohit, et al.
Published: (2026)
by: Bhattacharya, Rohit, et al.
Published: (2026)
Disentangle Estimation of Causal Effects from Cross-Silo Data
by: Liu, Yuxuan, et al.
Published: (2024)
by: Liu, Yuxuan, et al.
Published: (2024)
DCRMTA: Unbiased Causal Representation for Multi-touch Attribution
by: Tang, Jiaming
Published: (2024)
by: Tang, Jiaming
Published: (2024)
Estimating and Mitigating the Congestion Effect of Curbside Pick-ups and Drop-offs: A Causal Inference Approach
by: Liu, Xiaohui, et al.
Published: (2022)
by: Liu, Xiaohui, et al.
Published: (2022)
Beyond Means: Topological Causal Effects under Persistent-Homology Ignorability
by: Saki, Amir, et al.
Published: (2026)
by: Saki, Amir, et al.
Published: (2026)
On the Granularity of Causal Effect Identifiability
by: Chen, Yizuo, et al.
Published: (2025)
by: Chen, Yizuo, et al.
Published: (2025)
Causal Structure Representation Learning of Confounders in Latent Space for Recommendation
by: Xu, Hangtong, et al.
Published: (2023)
by: Xu, Hangtong, et al.
Published: (2023)
Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs
by: Ferreira, Simon, et al.
Published: (2024)
by: Ferreira, Simon, et al.
Published: (2024)
Identifying Conditional Causal Effects in MPDAGs
by: LaPlante, Sara, et al.
Published: (2025)
by: LaPlante, Sara, et al.
Published: (2025)
Transferring Causal Effects using Proxies
by: Iglesias-Alonso, Manuel, et al.
Published: (2025)
by: Iglesias-Alonso, Manuel, et al.
Published: (2025)
Learning Causal Abstractions of Linear Structural Causal Models
by: Massidda, Riccardo, et al.
Published: (2024)
by: Massidda, Riccardo, et al.
Published: (2024)
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network
by: Zhao, Yonghe, et al.
Published: (2023)
by: Zhao, Yonghe, et al.
Published: (2023)
Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding
by: Ferreira, Simon, et al.
Published: (2024)
by: Ferreira, Simon, et al.
Published: (2024)
Censoring-Aware Tree-Based Reinforcement Learning for Estimating Dynamic Treatment Regimes with Censored Outcomes
by: Paul, Animesh Kumar, et al.
Published: (2025)
by: Paul, Animesh Kumar, et al.
Published: (2025)
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables
by: Xie, Feng, et al.
Published: (2023)
by: Xie, Feng, et al.
Published: (2023)
s-ID: Causal Effect Identification in a Sub-Population
by: Abouei, Amir Mohammad, et al.
Published: (2023)
by: Abouei, Amir Mohammad, et al.
Published: (2023)
Fast Proxy Experiment Design for Causal Effect Identification
by: Elahi, Sepehr, et al.
Published: (2024)
by: Elahi, Sepehr, et al.
Published: (2024)
Similar Items
-
Causal Inference under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects
by: Kubota, Kohsuke, et al.
Published: (2025) -
Off-Policy Evaluation and Learning for Survival Outcomes under Censoring
by: Kubota, Kohsuke, et al.
Published: (2026) -
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks
by: Cui, Ziqiang, et al.
Published: (2024) -
Conformal Prediction for Causal Effects of Continuous Treatments
by: Schröder, Maresa, et al.
Published: (2024) -
Compositional Models for Estimating Causal Effects
by: Pruthi, Purva, et al.
Published: (2024)