Scalable Out-of-distribution Robustness in the Presence of Unobserved Confounders
Fuente:
arXiv
Saved in:
| Main Authors: | Prashant, Parjanya, Khatami, Seyedeh Baharan, Ribeiro, Bruno, Salimi, Babak |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
by: Khatami, Seyedeh Baharan, et al.
Published: (2024)
by: Khatami, Seyedeh Baharan, et al.
Published: (2024)
KAIROS: Scalable Model-Agnostic Data Valuation
by: Zhu, Jiongli, et al.
Published: (2025)
by: Zhu, Jiongli, et al.
Published: (2025)
A Lightweight Method to Disrupt Memorized Sequences in LLM
by: Prashant, Parjanya Prajakta, et al.
Published: (2025)
by: Prashant, Parjanya Prajakta, et al.
Published: (2025)
Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates
by: Prashant, Parjanya Prajakta, et al.
Published: (2026)
by: Prashant, Parjanya Prajakta, et al.
Published: (2026)
Towards Robust Offline Evaluation: A Causal and Information Theoretic Framework for Debiasing Ranking Systems
by: Khatami, Seyedeh Baharan, et al.
Published: (2025)
by: Khatami, Seyedeh Baharan, et al.
Published: (2025)
Peer Effect Estimation in the Presence of Simultaneous Feedback and Unobserved Confounders
by: Du, Xiaojing, et al.
Published: (2025)
by: Du, Xiaojing, et al.
Published: (2025)
Robust Design and Evaluation of Predictive Algorithms under Unobserved Confounding
by: Rambachan, Ashesh, et al.
Published: (2022)
by: Rambachan, Ashesh, et al.
Published: (2022)
Auditing Fairness under Unobserved Confounding
by: Byun, Yewon, et al.
Published: (2024)
by: Byun, Yewon, et al.
Published: (2024)
Detecting Unobserved Confounders: A Kernelized Regression Approach
by: Chen, Yikai, et al.
Published: (2026)
by: Chen, Yikai, et al.
Published: (2026)
Robust Fitted-Q-Evaluation and Iteration under Sequentially Exogenous Unobserved Confounders
by: Bruns-Smith, David, et al.
Published: (2023)
by: Bruns-Smith, David, et al.
Published: (2023)
Differentiable Causal Discovery For Latent Hierarchical Causal Models
by: Prashant, Parjanya, et al.
Published: (2024)
by: Prashant, Parjanya, et al.
Published: (2024)
Efficient and Sharp Off-Policy Learning under Unobserved Confounding
by: Hess, Konstantin, et al.
Published: (2025)
by: Hess, Konstantin, et al.
Published: (2025)
Causal Inference with Categorical Unobserved Confounder via Mixture Learning
by: Saha, Aytijhya, et al.
Published: (2026)
by: Saha, Aytijhya, et al.
Published: (2026)
Sensitivity Analysis to Unobserved Confounding with Copula-based Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2025)
by: Balgi, Sourabh, et al.
Published: (2025)
Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise
by: Xue, Yihao, et al.
Published: (2022)
by: Xue, Yihao, et al.
Published: (2022)
Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding
by: Schkoda, Daniela, et al.
Published: (2024)
by: Schkoda, Daniela, et al.
Published: (2024)
Copula-ResLogit: A Deep-Copula Framework for Unobserved Confounding Effects
by: Kamal, Kimia, et al.
Published: (2026)
by: Kamal, Kimia, et al.
Published: (2026)
Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
by: Donnelly, Jon, et al.
Published: (2025)
by: Donnelly, Jon, et al.
Published: (2025)
Causal Imitation Learning under Expert-Observable and Expert-Unobservable Confounding
by: Shao, Daqian, et al.
Published: (2025)
by: Shao, Daqian, et al.
Published: (2025)
Estimating Individual Dose-Response Curves under Unobserved Confounders from Observational Data
by: Chen, Shutong, et al.
Published: (2024)
by: Chen, Shutong, et al.
Published: (2024)
Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status
by: Lee, Samuel, et al.
Published: (2024)
by: Lee, Samuel, et al.
Published: (2024)
Scalable Differentiable Causal Discovery in the Presence of Latent Confounders with Skeleton Posterior (Extended Version)
by: Ma, Pingchuan, et al.
Published: (2024)
by: Ma, Pingchuan, et al.
Published: (2024)
Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework
by: Schröder, Maresa, et al.
Published: (2023)
by: Schröder, Maresa, et al.
Published: (2023)
Challenges and Opportunities in Improving Worst-Group Generalization in Presence of Spurious Features
by: Joshi, Siddharth, et al.
Published: (2023)
by: Joshi, Siddharth, et al.
Published: (2023)
$ρ$-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows
by: Balgi, Sourabh, et al.
Published: (2022)
by: Balgi, Sourabh, et al.
Published: (2022)
Gene Regulatory Network Inference in the Presence of Selection Bias and Latent Confounders
by: Luo, Gongxu, et al.
Published: (2025)
by: Luo, Gongxu, et al.
Published: (2025)
Out-of-distribution detection using normalizing flows on the data manifold
by: Razavi, Seyedeh Fatemeh, et al.
Published: (2023)
by: Razavi, Seyedeh Fatemeh, et al.
Published: (2023)
Understanding the Robustness of Multi-modal Contrastive Learning to Distribution Shift
by: Xue, Yihao, et al.
Published: (2023)
by: Xue, Yihao, et al.
Published: (2023)
Bad Habits: Policy Confounding and Out-of-Trajectory Generalization in RL
by: Suau, Miguel, et al.
Published: (2023)
by: Suau, Miguel, et al.
Published: (2023)
Regression-Based Estimation of Causal Effects in the Presence of Selection Bias and Confounding
by: Hafer, Marlies, et al.
Published: (2025)
by: Hafer, Marlies, et al.
Published: (2025)
Graph Contrastive Learning under Heterophily via Graph Filters
by: Yang, Wenhan, et al.
Published: (2023)
by: Yang, Wenhan, et al.
Published: (2023)
dcFCI: Robust Causal Discovery Under Latent Confounding, Unfaithfulness, and Mixed Data
by: Ribeiro, Adèle H., et al.
Published: (2025)
by: Ribeiro, Adèle H., et al.
Published: (2025)
Stress-Testing ML Pipelines with Adversarial Data Corruption
by: Zhu, Jiongli, et al.
Published: (2025)
by: Zhu, Jiongli, et al.
Published: (2025)
Learning from Uncertain Data: From Possible Worlds to Possible Models
by: Zhu, Jiongli, et al.
Published: (2024)
by: Zhu, Jiongli, et al.
Published: (2024)
A Convex Framework for Confounding Robust Inference
by: Ishikawa, Kei, et al.
Published: (2023)
by: Ishikawa, Kei, et al.
Published: (2023)
Topology-aware Robust Optimization for Out-of-distribution Generalization
by: Qiao, Fengchun, et al.
Published: (2023)
by: Qiao, Fengchun, et al.
Published: (2023)
Data-Efficient Contrastive Self-supervised Learning: Most Beneficial Examples for Supervised Learning Contribute the Least
by: Joshi, Siddharth, et al.
Published: (2023)
by: Joshi, Siddharth, et al.
Published: (2023)
Tuning the Implicit Regularizer of Masked Diffusion Language Models: Enhancing Generalization via Insights from $k$-Parity
by: Huang, Jianhao, et al.
Published: (2026)
by: Huang, Jianhao, et al.
Published: (2026)
Robust Personalized Recommendation under Hidden Confounding in MNAR
by: Li, Zongyu, et al.
Published: (2026)
by: Li, Zongyu, et al.
Published: (2026)
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-Training of Deep Networks
by: Joshi, Siddharth, et al.
Published: (2024)
by: Joshi, Siddharth, et al.
Published: (2024)
Similar Items
-
Graph Machine Learning based Doubly Robust Estimator for Network Causal Effects
by: Khatami, Seyedeh Baharan, et al.
Published: (2024) -
KAIROS: Scalable Model-Agnostic Data Valuation
by: Zhu, Jiongli, et al.
Published: (2025) -
A Lightweight Method to Disrupt Memorized Sequences in LLM
by: Prashant, Parjanya Prajakta, et al.
Published: (2025) -
Fine-Tuning Without Forgetting via Loss-Adaptive Learning Rates
by: Prashant, Parjanya Prajakta, et al.
Published: (2026) -
Towards Robust Offline Evaluation: A Causal and Information Theoretic Framework for Debiasing Ranking Systems
by: Khatami, Seyedeh Baharan, et al.
Published: (2025)