Estimating Treatment Effects with Independent Component Analysis
Fuente:
arXiv
Saved in:
| Main Authors: | Reizinger, Patrik, Mackey, Lester, Brendel, Wieland, Krishnan, Rahul |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research
by: Reizinger, Patrik, et al.
Published: (2025)
by: Reizinger, Patrik, et al.
Published: (2025)
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning
by: Reizinger, Patrik, et al.
Published: (2024)
by: Reizinger, Patrik, et al.
Published: (2024)
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis
by: Rajendran, Goutham, et al.
Published: (2023)
by: Rajendran, Goutham, et al.
Published: (2023)
Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning
by: Reizinger, Patrik, et al.
Published: (2025)
by: Reizinger, Patrik, et al.
Published: (2025)
Cross-Entropy Is All You Need To Invert the Data Generating Process
by: Reizinger, Patrik, et al.
Published: (2024)
by: Reizinger, Patrik, et al.
Published: (2024)
Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts
by: Mészáros, Anna, et al.
Published: (2024)
by: Mészáros, Anna, et al.
Published: (2024)
Position: Understanding LLMs Requires More Than Statistical Generalization
by: Reizinger, Patrik, et al.
Published: (2024)
by: Reizinger, Patrik, et al.
Published: (2024)
Who Guards the Guardians? The Challenges of Evaluating Identifiability of Learned Representations
by: Joshi, Shruti, et al.
Published: (2026)
by: Joshi, Shruti, et al.
Published: (2026)
Causality is Key for Interpretability Claims to Generalise
by: Joshi, Shruti, et al.
Published: (2026)
by: Joshi, Shruti, et al.
Published: (2026)
MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model
by: Mayilvahanan, Prasanna, et al.
Published: (2025)
by: Mayilvahanan, Prasanna, et al.
Published: (2025)
SureMap: Simultaneous Mean Estimation for Single-Task and Multi-Task Disaggregated Evaluation
by: Khodak, Mikhail, et al.
Published: (2024)
by: Khodak, Mikhail, et al.
Published: (2024)
InfoNCE: Identifying the Gap Between Theory and Practice
by: Rusak, Evgenia, et al.
Published: (2024)
by: Rusak, Evgenia, et al.
Published: (2024)
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws
by: Mayilvahanan, Prasanna, et al.
Published: (2025)
by: Mayilvahanan, Prasanna, et al.
Published: (2025)
From Isolation to Entanglement: When Do Interpretability Methods Identify and Disentangle Known Concepts?
by: Mueller, Aaron, et al.
Published: (2025)
by: Mueller, Aaron, et al.
Published: (2025)
Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?
by: Mayilvahanan, Prasanna, et al.
Published: (2023)
by: Mayilvahanan, Prasanna, et al.
Published: (2023)
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes
by: Chauhan, Vinod Kumar, et al.
Published: (2025)
by: Chauhan, Vinod Kumar, et al.
Published: (2025)
Informed Correctors for Discrete Diffusion Models
by: Zhao, Yixiu, et al.
Published: (2024)
by: Zhao, Yixiu, et al.
Published: (2024)
Self-Taught Optimizer (STOP): Recursively Self-Improving Code Generation
by: Zelikman, Eric, et al.
Published: (2023)
by: Zelikman, Eric, et al.
Published: (2023)
SurvHTE-Bench: A Benchmark for Heterogeneous Treatment Effect Estimation in Survival Analysis
by: Noroozizadeh, Shahriar, et al.
Published: (2026)
by: Noroozizadeh, Shahriar, et al.
Published: (2026)
Disentangled Graph Autoencoder for Treatment Effect Estimation
by: Fan, Di, et al.
Published: (2024)
by: Fan, Di, et al.
Published: (2024)
Treatment Effect Estimation with Differentiated Networked Effect on Graph Data
by: Lin, Xiaofeng, et al.
Published: (2026)
by: Lin, Xiaofeng, et al.
Published: (2026)
Measurement Scheduling for ICU Patients with Offline Reinforcement Learning
by: Ji, Zongliang, et al.
Published: (2024)
by: Ji, Zongliang, et al.
Published: (2024)
Deep Disentangled Representation Network for Treatment Effect Estimation
by: Meng, Hui, et al.
Published: (2025)
by: Meng, Hui, et al.
Published: (2025)
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
by: Melnychuk, Valentyn, et al.
Published: (2023)
by: Melnychuk, Valentyn, et al.
Published: (2023)
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)
Adapting Language Models via Token Translation
by: Feng, Zhili, et al.
Published: (2024)
by: Feng, Zhili, et al.
Published: (2024)
Discrete Speech Unit Extraction via Independent Component Analysis
by: Nakamura, Tomohiko, et al.
Published: (2025)
by: Nakamura, Tomohiko, et al.
Published: (2025)
Confounder Detection via Treatment Intent: A New Observational Study Design
by: Plecko, Drago, et al.
Published: (2026)
by: Plecko, Drago, et al.
Published: (2026)
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect Estimation
by: Hsu, Chan, et al.
Published: (2024)
by: Hsu, Chan, et al.
Published: (2024)
Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation
by: Wang, Hao, et al.
Published: (2024)
by: Wang, Hao, et al.
Published: (2024)
Real vs. Semi-Simulated: Rethinking Evaluation for Treatment Effect Estimation
by: Panagopoulos, George
Published: (2026)
by: Panagopoulos, George
Published: (2026)
Causal Component Analysis
by: Wendong, Liang, et al.
Published: (2023)
by: Wendong, Liang, et al.
Published: (2023)
Road User Classification from High-Frequency GNSS Data Using Distributed Edge Intelligence
by: Köpper, Lennart, et al.
Published: (2024)
by: Köpper, Lennart, et al.
Published: (2024)
Don't trust your eyes: on the (un)reliability of feature visualizations
by: Geirhos, Robert, et al.
Published: (2023)
by: Geirhos, Robert, et al.
Published: (2023)
Conformal Diffusion Models for Individual Treatment Effect Estimation and Inference
by: Cai, Hengrui, et al.
Published: (2024)
by: Cai, Hengrui, et al.
Published: (2024)
PIPCFR: Pseudo-outcome Imputation with Post-treatment Variables for Individual Treatment Effect Estimation
by: Lin, Zichuan, et al.
Published: (2025)
by: Lin, Zichuan, et al.
Published: (2025)
Pareto-Optimal Estimation and Policy Learning on Short-term and Long-term Treatment Effects
by: Wang, Yingrong, et al.
Published: (2024)
by: Wang, Yingrong, et al.
Published: (2024)
Mixture Proportion Estimation and Weakly-supervised Kernel Test for Conditional Independence
by: Hirose, Yushi, et al.
Published: (2026)
by: Hirose, Yushi, et al.
Published: (2026)
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)
Similar Items
-
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self-Supervised Learning Research
by: Reizinger, Patrik, et al.
Published: (2025) -
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning
by: Reizinger, Patrik, et al.
Published: (2024) -
An Interventional Perspective on Identifiability in Gaussian LTI Systems with Independent Component Analysis
by: Rajendran, Goutham, et al.
Published: (2023) -
Skill Learning via Policy Diversity Yields Identifiable Representations for Reinforcement Learning
by: Reizinger, Patrik, et al.
Published: (2025) -
Cross-Entropy Is All You Need To Invert the Data Generating Process
by: Reizinger, Patrik, et al.
Published: (2024)