PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression
Fuente:
arXiv
Saved in:
| Main Authors: | Fumagalli, Fabian, Witter, R. Teal, Musco, Christopher |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions
by: Fumagalli, Fabian, et al.
Published: (2024)
by: Fumagalli, Fabian, et al.
Published: (2024)
Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
by: Witter, R. Teal, et al.
Published: (2025)
by: Witter, R. Teal, et al.
Published: (2025)
Provably Accurate Shapley Value Estimation via Leverage Score Sampling
by: Musco, Christopher, et al.
Published: (2024)
by: Musco, Christopher, et al.
Published: (2024)
Improving the Weighting Strategy in KernelSHAP
by: Olsen, Lars Henry Berge, et al.
Published: (2024)
by: Olsen, Lars Henry Berge, et al.
Published: (2024)
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
by: Wever, Marcel, et al.
Published: (2025)
by: Wever, Marcel, et al.
Published: (2025)
Kernel Banzhaf: A Fast and Robust Estimator for Banzhaf Values
by: Liu, Yurong, et al.
Published: (2024)
by: Liu, Yurong, et al.
Published: (2024)
Interaction Tensor SHAP
by: Hasegawa, Hiroki, et al.
Published: (2025)
by: Hasegawa, Hiroki, et al.
Published: (2025)
CS-SHAP: Extending SHAP to Cyclic-Spectral Domain for Better Interpretability of Intelligent Fault Diagnosis
by: Chen, Qian, et al.
Published: (2025)
by: Chen, Qian, et al.
Published: (2025)
Proxy-Based Approximation of Shapley and Banzhaf Interactions
by: Thies, Santo M. A. R., et al.
Published: (2026)
by: Thies, Santo M. A. R., et al.
Published: (2026)
Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm
by: Witter, R. Teal, et al.
Published: (2024)
by: Witter, R. Teal, et al.
Published: (2024)
An Odd Estimator for Shapley Values
by: Fumagalli, Fabian, et al.
Published: (2026)
by: Fumagalli, Fabian, et al.
Published: (2026)
A Polynomial-Time Axiomatic Alternative to SHAP for Feature Attribution
by: Hiraki, Kazuhiro, et al.
Published: (2026)
by: Hiraki, Kazuhiro, et al.
Published: (2026)
Efficient KernelSHAP Explanations for Patch-based 3D Medical Image Segmentation
by: Brioso, Ricardo Coimbra, et al.
Published: (2026)
by: Brioso, Ricardo Coimbra, et al.
Published: (2026)
Exactly Computing do-Shapley Values
by: Witter, R. Teal, et al.
Published: (2026)
by: Witter, R. Teal, et al.
Published: (2026)
Towards trustable SHAP scores
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
ContextualSHAP : Enhancing SHAP Explanations Through Contextual Language Generation
by: Dwiyanti, Latifa, et al.
Published: (2025)
by: Dwiyanti, Latifa, et al.
Published: (2025)
Explanation Multiplicity in SHAP: Characterization and Assessment
by: Hwang, Hyunseung, et al.
Published: (2026)
by: Hwang, Hyunseung, et al.
Published: (2026)
Can Global XAI Methods Reveal Injected Bias in LLMs? SHAP vs Rule Extraction vs RuleSHAP
by: Sovrano, Francesco
Published: (2025)
by: Sovrano, Francesco
Published: (2025)
SHAP-based Explanations are Sensitive to Feature Representation
by: Hwang, Hyunseung, et al.
Published: (2025)
by: Hwang, Hyunseung, et al.
Published: (2025)
From SHAP Scores to Feature Importance Scores
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
On the Tractability of SHAP Explanations under Markovian Distributions
by: Marzouk, Reda, et al.
Published: (2024)
by: Marzouk, Reda, et al.
Published: (2024)
Fooling SHAP with Output Shuffling Attacks
by: Yuan, Jun, et al.
Published: (2024)
by: Yuan, Jun, et al.
Published: (2024)
TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions
by: Heidari, Farzaneh, et al.
Published: (2026)
by: Heidari, Farzaneh, et al.
Published: (2026)
Towards Piece-by-Piece Explanations for Chess Positions with SHAP
by: Spinnato, Francesco
Published: (2025)
by: Spinnato, Francesco
Published: (2025)
How to safely discard features based on aggregate SHAP values
by: Bhattacharjee, Robi, et al.
Published: (2025)
by: Bhattacharjee, Robi, et al.
Published: (2025)
SHAP scores fail pervasively even when Lipschitz succeeds
by: Letoffe, Olivier, et al.
Published: (2024)
by: Letoffe, Olivier, et al.
Published: (2024)
A Perspective on Explainable Artificial Intelligence Methods: SHAP and LIME
by: Salih, Ahmed, et al.
Published: (2023)
by: Salih, Ahmed, et al.
Published: (2023)
Enhancing SHAP Explainability for Diagnostic and Prognostic ML Models in Alzheimer Disease
by: Guillén, Pablo, et al.
Published: (2026)
by: Guillén, Pablo, et al.
Published: (2026)
CQD-SHAP: Explainable Complex Query Answering via Shapley Values
by: Abbasi, Parsa, et al.
Published: (2025)
by: Abbasi, Parsa, et al.
Published: (2025)
Beyond TreeSHAP: Efficient Computation of Any-Order Shapley Interactions for Tree Ensembles
by: Muschalik, Maximilian, et al.
Published: (2024)
by: Muschalik, Maximilian, et al.
Published: (2024)
CNN-TFT explained by SHAP with multi-head attention weights for time series forecasting
by: Stefenon, Stefano F., et al.
Published: (2025)
by: Stefenon, Stefano F., et al.
Published: (2025)
Shaping Up SHAP: Enhancing Stability through Layer-Wise Neighbor Selection
by: Kelodjou, Gwladys, et al.
Published: (2023)
by: Kelodjou, Gwladys, et al.
Published: (2023)
DeltaSHAP: Explaining Prediction Evolutions in Online Patient Monitoring with Shapley Values
by: Kim, Changhun, et al.
Published: (2025)
by: Kim, Changhun, et al.
Published: (2025)
Enhancing RL Generalizability in Robotics through SHAP Analysis of Algorithms and Hyperparameters
by: Kong, Lingxiao, et al.
Published: (2026)
by: Kong, Lingxiao, et al.
Published: (2026)
Causal SHAP: Feature Attribution with Dependency Awareness through Causal Discovery
by: Ng, Woon Yee, et al.
Published: (2025)
by: Ng, Woon Yee, et al.
Published: (2025)
Choose Your Explanation: A Comparison of SHAP and GradCAM in Human Activity Recognition
by: Tempel, Felix, et al.
Published: (2024)
by: Tempel, Felix, et al.
Published: (2024)
FairSHAP: Preprocessing for Fairness Through Attribution-Based Data Augmentation
by: Zhu, Lin, et al.
Published: (2025)
by: Zhu, Lin, et al.
Published: (2025)
Interpretable Physics-Informed Load Forecasting for U.S. Grid Resilience: SHAP-Guided Ensemble Validation in Hybrid Deep Learning Under Extreme Weather
by: Abubakkar, Md, et al.
Published: (2026)
by: Abubakkar, Md, et al.
Published: (2026)
Verified SHAP: Provable Bounds for Exact Shapley Values of Neural Networks
by: Boetius, David, et al.
Published: (2026)
by: Boetius, David, et al.
Published: (2026)
Quantifying Cross-Modal Interactions in Multimodal Glioma Survival Prediction via InterSHAP: Evidence for Additive Signal Integration
by: Swift, Iain, et al.
Published: (2026)
by: Swift, Iain, et al.
Published: (2026)
Similar Items
-
KernelSHAP-IQ: Weighted Least-Square Optimization for Shapley Interactions
by: Fumagalli, Fabian, et al.
Published: (2024) -
Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values
by: Witter, R. Teal, et al.
Published: (2025) -
Provably Accurate Shapley Value Estimation via Leverage Score Sampling
by: Musco, Christopher, et al.
Published: (2024) -
Improving the Weighting Strategy in KernelSHAP
by: Olsen, Lars Henry Berge, et al.
Published: (2024) -
HyperSHAP: Shapley Values and Interactions for Explaining Hyperparameter Optimization
by: Wever, Marcel, et al.
Published: (2025)