Missingness Bias Calibration in Feature Attribution Explanations
Fuente:
arXiv
Saved in:
| Main Authors: | Sridhar, Shailesh, Xue, Anton, Wong, Eric |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Probabilistic Stability Guarantees for Feature Attributions
by: Jin, Helen, et al.
Published: (2025)
by: Jin, Helen, et al.
Published: (2025)
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties
by: Ji, Xiayan, et al.
Published: (2024)
by: Ji, Xiayan, et al.
Published: (2024)
Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data
by: Genans, Ferdinand, et al.
Published: (2026)
by: Genans, Ferdinand, et al.
Published: (2026)
Model-Based Counterfactual Explanations Incorporating Feature Space Attributes for Tabular Data
by: Sumiya, Yuta, et al.
Published: (2024)
by: Sumiya, Yuta, et al.
Published: (2024)
Disentangling Interactions and Dependencies in Feature Attribution
by: König, Gunnar, et al.
Published: (2024)
by: König, Gunnar, et al.
Published: (2024)
Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups
by: You, Weiqiu, et al.
Published: (2023)
by: You, Weiqiu, et al.
Published: (2023)
Provably Better Explanations with Optimized Aggregation of Feature Attributions
by: Decker, Thomas, et al.
Published: (2024)
by: Decker, Thomas, et al.
Published: (2024)
Hypothesis Class Determines Explanation: Why Accurate Models Disagree on Feature Attribution
by: B, Thackshanaramana
Published: (2026)
by: B, Thackshanaramana
Published: (2026)
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation
by: Chen, Xuexin, et al.
Published: (2024)
by: Chen, Xuexin, et al.
Published: (2024)
Domain Adaptation Under MNAR Missingness
by: Stokes, Tyrel, et al.
Published: (2025)
by: Stokes, Tyrel, et al.
Published: (2025)
Nearly Optimal Bayesian Inference for Structural Missingness
by: Liang, Chen, et al.
Published: (2026)
by: Liang, Chen, et al.
Published: (2026)
MCCE: Missingness-aware Causal Concept Explainer
by: Gao, Jifan, et al.
Published: (2024)
by: Gao, Jifan, et al.
Published: (2024)
Beyond Attribution: Unified Concept-Level Explanations
by: Liu, Junhao, et al.
Published: (2024)
by: Liu, Junhao, et al.
Published: (2024)
Quantifying Potential Observation Missingness in Inverse Reinforcement Learning
by: Benac, Leo, et al.
Published: (2026)
by: Benac, Leo, et al.
Published: (2026)
Multi-Station WiFi CSI Sensing Framework Robust to Station-wise Feature Missingness and Limited Labeled Data
by: Kayano, Keita, et al.
Published: (2026)
by: Kayano, Keita, et al.
Published: (2026)
Fair Graph Machine Learning under Adversarial Missingness Processes
by: Lina, Debolina Halder, et al.
Published: (2023)
by: Lina, Debolina Halder, et al.
Published: (2023)
Calibrated Explanations: with Uncertainty Information and Counterfactuals
by: Lofstrom, Helena, et al.
Published: (2023)
by: Lofstrom, Helena, et al.
Published: (2023)
The Attribution Contract: Feature Attribution for Generative Language Models
by: Nguyen, Giang
Published: (2026)
by: Nguyen, Giang
Published: (2026)
Minimizing False-Positive Attributions in Explanations of Non-Linear Models
by: Gjølbye, Anders, et al.
Published: (2025)
by: Gjølbye, Anders, et al.
Published: (2025)
Backward Compatibility in Attributive Explanation and Enhanced Model Training Method
by: Matsuno, Ryuta
Published: (2024)
by: Matsuno, Ryuta
Published: (2024)
AGOP as Explanation: From Feature Learning to Per-Sample Attribution in Image Classifiers
by: Katakam, Raj Kiran Gupta
Published: (2026)
by: Katakam, Raj Kiran Gupta
Published: (2026)
Conditional Imputation for Within-Modality Missingness in Multi-Modal Federated Learning
by: Zheng, Wugeng, et al.
Published: (2026)
by: Zheng, Wugeng, et al.
Published: (2026)
MIRRAMS: Learning Robust Tabular Models under Unseen Missingness Shifts
by: Lee, Jihye, et al.
Published: (2025)
by: Lee, Jihye, et al.
Published: (2025)
GRU-D Characterizes Age-Specific Temporal Missingness in MIMIC-IV
by: Giesa, Niklas, et al.
Published: (2024)
by: Giesa, Niklas, et al.
Published: (2024)
Beyond Random Missingness: Clinically Rethinking for Healthcare Time Series Imputation
by: Qian, Linglong, et al.
Published: (2024)
by: Qian, Linglong, et al.
Published: (2024)
Exploiting Missing Data Remediation Strategies using Adversarial Missingness Attacks
by: Koyuncu, Deniz, et al.
Published: (2024)
by: Koyuncu, Deniz, et al.
Published: (2024)
Understanding Missingness in Time-series Electronic Health Records for Individualized Representation
by: Ghosheh, Ghadeer O., et al.
Published: (2024)
by: Ghosheh, Ghadeer O., et al.
Published: (2024)
Membership Inference Attacks on Discrete Diffusion Language Models
by: Kasivelrajan, Shailesh
Published: (2026)
by: Kasivelrajan, Shailesh
Published: (2026)
Imputation of Unknown Missingness in Sparse Electronic Health Records
by: Han, Jun, et al.
Published: (2026)
by: Han, Jun, et al.
Published: (2026)
Missingness-MDPs: Bridging the Theory of Missing Data and POMDPs
by: Wendland, Joshua, et al.
Published: (2026)
by: Wendland, Joshua, et al.
Published: (2026)
AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments
by: Zhang, Yang, et al.
Published: (2023)
by: Zhang, Yang, et al.
Published: (2023)
On the Robustness of Global Feature Effect Explanations
by: Baniecki, Hubert, et al.
Published: (2024)
by: Baniecki, Hubert, et al.
Published: (2024)
A Compression Perspective on Simplicity Bias
by: Marty, Tom, et al.
Published: (2026)
by: Marty, Tom, et al.
Published: (2026)
When Explanations Lie: Why Many Modified BP Attributions Fail
by: Sixt, Leon, et al.
Published: (2019)
by: Sixt, Leon, et al.
Published: (2019)
Unifying Attribution-Based Explanations Using Functional Decomposition
by: Gevaert, Arne, et al.
Published: (2024)
by: Gevaert, Arne, et al.
Published: (2024)
Calibrated Explanations for Regression
by: Löfström, Tuwe, et al.
Published: (2023)
by: Löfström, Tuwe, et al.
Published: (2023)
GradCFA: A Hybrid Gradient-Based Counterfactual and Feature Attribution Explanation Algorithm for Local Interpretation of Neural Networks
by: Sanderson, Jacob, et al.
Published: (2026)
by: Sanderson, Jacob, et al.
Published: (2026)
Feature Attribution from First Principles
by: Taimeskhanov, Magamed, et al.
Published: (2025)
by: Taimeskhanov, Magamed, et al.
Published: (2025)
Blockwise Missingness meets AI: A Tractable Solution for Semiparametric Inference
by: Xu, Qi, et al.
Published: (2025)
by: Xu, Qi, et al.
Published: (2025)
Mixed Matrix Completion in Complex Survey Sampling under Heterogeneous Missingness
by: Mao, Xiaojun, et al.
Published: (2024)
by: Mao, Xiaojun, et al.
Published: (2024)
Similar Items
-
Probabilistic Stability Guarantees for Feature Attributions
by: Jin, Helen, et al.
Published: (2025) -
AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties
by: Ji, Xiayan, et al.
Published: (2024) -
Increasing Missingness to Reduce Bias: Richardson-SGD with Missing Data
by: Genans, Ferdinand, et al.
Published: (2026) -
Model-Based Counterfactual Explanations Incorporating Feature Space Attributes for Tabular Data
by: Sumiya, Yuta, et al.
Published: (2024) -
Disentangling Interactions and Dependencies in Feature Attribution
by: König, Gunnar, et al.
Published: (2024)