SOTAVerified

Feature Importance

Papers

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Showing 151–200 of 890 papers

TitleStatusHype
STAA: Spatio-Temporal Attention Attribution for Real-Time Interpreting Transformer-based Video ModelsCode0
Enhancing Osteoporosis Detection: An Explainable Multi-Modal Learning Framework with Feature Fusion and Variable Clustering—0
Disentangling Interactions and Dependencies in Feature AttributionCode0
Development and Comparative Analysis of Machine Learning Models for Hypoxemia Severity Triage in CBRNE Emergency Scenarios Using Physiological and Demographic Data from Medical-Grade Devices—0
High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented TransformerCode1
EEG-based Multimodal Representation Learning for Emotion Recognition—0
Feature Responsiveness Scores: Model-Agnostic Explanations for RecourseCode0
Going Beyond H&E and Oncology: How Do Histopathology Foundation Models Perform for Multi-stain IHC and Immunology?Code1
Fast Calibrated Explanations: Efficient and Uncertainty-Aware Explanations for Machine Learning ModelsCode2
Data-Driven Transient Stability Assessment of Power Systems with a Novel GHM-Enhanced CatBoost Algorithm—0
Omics-driven hybrid dynamic modeling of bioprocesses with uncertainty estimation—0
QIXAI: A Quantum-Inspired Framework for Enhancing Classical and Quantum Model Transparency and Understanding—0
Mixed Attention Transformer Enhanced Channel Estimation for Extremely Large-Scale MIMO Systems—0
Building Trust in Black-box Optimization: A Comprehensive Framework for Explainability—0
Interpreting Inflammation Prediction Model via Tag-based Cohort Explanation—0
Global Censored Quantile Random Forest—0
A Multi-Task Text Classification Pipeline with Natural Language Explanations: A User-Centric Evaluation in Sentiment Analysis and Offensive Language Identification in Greek Tweets—0
Unlearning-based Neural Interpretations—0
Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual ExplanationsCode1
An Approach To Enhance IoT Security In 6G Networks Through Explainable AI—0
Benchmarking the Fidelity and Utility of Synthetic Relational DataCode0
Nonparametric IPSS: Fast, flexible feature selection with false discovery controlCode0
Enhancing End Stage Renal Disease Outcome Prediction: A Multi-Sourced Data-Driven Approach—0
Integrating Protein Sequence and Expression Level to Analysis Molecular Characterization of Breast Cancer Subtypes—0
Sufficient and Necessary Explanations (and What Lies in Between)—0
All-in-One Image Coding for Joint Human-Machine Vision with Multi-Path AggregationCode1
Implementing NLPs in industrial process modeling: Addressing Categorical Variables—0
Random Forest Regression Feature Importance for Climate Impact Pathway Detection—0
Explaining word embeddings with perfect fidelity: Case study in research impact predictionCode0
Generative LLM Powered Conversational AI Application for Personalized Risk Assessment: A Case Study in COVID-19—0
Validity of Feature Importance in Low-Performing Machine Learning for Tabular Biomedical Data—0
Efficient Milling Quality Prediction with Explainable Machine Learning—0
MusicLIME: Explainable Multimodal Music UnderstandingCode1
Mapping Biomedical Ontology Terms to IDs: Effect of Domain Prevalence on Prediction Accuracy—0
Feature Importance in Pedestrian Intention Prediction: A Context-Aware Review—0
Effect of Clinical History on Predictive Model Performance for Renal Complications of Diabetes—0
Leveraging Interpretability in the Transformer to Automate the Proactive Scaling of Cloud Resources—0
Optimizing Mortality Prediction for ICU Heart Failure Patients: Leveraging XGBoost and Advanced Machine Learning with the MIMIC-III Database—0
From Predictive Importance to Causality: Which Machine Learning Model Reflects Reality?—0
Error-controlled non-additive interaction discovery in machine learning models—0
An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated TextCode0
Augmented Functional Random Forests: Classifier Construction and Unbiased Functional Principal Components Importance through Ad-Hoc Conditional Permutations—0
Counterfactuals As a Means for Evaluating Faithfulness of Attribution Methods in Autoregressive Language ModelsCode0
DTN: Deep Multiple Task-specific Feature Interactions Network for Multi-Task Recommendation—0
Approximation of the Proximal Operator of the _ Norm Using a Neural NetworkCode0
Shapley Marginal Surplus for Strong Models—0
Cognitive Networks and Performance Drive fMRI-Based State Classification Using DNN Models—0
A Pipeline for Data-Driven Learning of Topological Features with Applications to Protein Stability Prediction—0
Unveiling the Power of Sparse Neural Networks for Feature SelectionCode0
Time is Not Enough: Time-Frequency based Explanation for Time-Series Black-Box ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Garson Variable ImportancePearson Correlation0.76—Unverified
2VarImpVIANNPearson Correlation0.76—Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.6—Unverified
2Garson Variable ImportancePearson Correlation0.22—Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.86—Unverified
2Garson Variable ImportancePearson Correlation0.64—Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.83—Unverified
2Garson Variable ImportancePearson Correlation0.6—Unverified
#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.9—Unverified
2Garson Variable ImportancePearson Correlation0.73—Unverified
#ModelMetricClaimedVerifiedStatus
1Garson Variable ImportancePearson Correlation0.74—Unverified
2VarImpVIANNPearson Correlation0.41—Unverified