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Feature Importance

Papers

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Showing 451–500 of 890 papers

TitleStatusHype
Segment Anything in Pathology Images with Natural Language—0
Self-FuseNet: Data Free Unsupervised Remote Sensing Image Super-Resolution—0
Semantically-Aware Game Image Quality Assessment—0
Semantic Interpretation and Validation of Graph Attention-based Explanations for GNN Models—0
Semantic match: Debugging feature attribution methods in XAI for healthcare—0
SemHARQ: Semantic-Aware HARQ for Multi-task Semantic Communications—0
Semi-Supervised Graph Representation Learning with Human-centric Explanation for Predicting Fatty Liver Disease—0
SensAI+Expanse Adaptation on Human Behaviour Towards Emotional Valence Prediction—0
SensAI+Expanse Emotional Valence Prediction Studies with Cognition and Memory Integration—0
SentiDrop: A Multi Modal Machine Learning model for Predicting Dropout in Distance Learning—0
Sentiment analysis of texts from social networks based on machine learning methods for monitoring public sentiment—0
SHAP@k:Efficient and Probably Approximately Correct (PAC) Identification of Top-k Features—0
Shapley Marginal Surplus for Strong Models—0
Shapley Residuals: Quantifying the limits of the Shapley value for explanations—0
SIDEs: Separating Idealization from Deceptive Explanations in xAI—0
Similarity of Neural Architectures using Adversarial Attack Transferability—0
Single Sample Feature Importance: An Interpretable Algorithm for Low-Level Feature Analysis—0
S&P 500 Trend Prediction—0
Spatial Association Between Near-Misses and Accident Blackspots in Sydney, Australia: A Getis-Ord G_i^* Analysis—0
Spatially-Coupled Neural Network Architectures—0
Spending Privacy Budget Fairly and Wisely—0
Stacking with Neural network for Cryptocurrency investment—0
Statistical and Machine Learning Models for Predicting Fire and Other Emergency Events—0
STRisk: A Socio-Technical Approach to Assess Hacking Breaches Risk—0
Structural Knowledge Distillation for Object Detection—0
Study of Feature Importance for Quantum Machine Learning Models—0
Sub-Seasonal Climate Forecasting via Machine Learning: Challenges, Analysis, and Advances—0
Sufficient and Necessary Explanations (and What Lies in Between)—0
Surrogate-assisted performance prediction for data-driven knowledge discovery algorithms: application to evolutionary modeling of clinical pathways—0
SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping—0
Symbolic Metamodels for Interpreting Black-boxes Using Primitive Functions—0
TabulaTime: A Novel Multimodal Deep Learning Framework for Advancing Acute Coronary Syndrome Prediction through Environmental and Clinical Data Integration—0
Text Analysis and Automatic Triage of Posts in a Mental Health Forum—0
The impact of feature importance methods on the interpretation of defect classifiers—0
The Role of Explanation Styles and Perceived Accuracy on Decision Making in Predictive Process Monitoring—0
The Role of User Profile for Fake News Detection—0
The utility of wearable devices in assessing ambulatory impairments of people with multiple sclerosis in free-living conditions—0
The Yield Curve as a Recession Leading Indicator. An Application for Gradient Boosting and Random Forest—0
Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations—0
TIGTEC : Token Importance Guided TExt Counterfactuals—0
TII-SSRC-23 Dataset: Typological Exploration of Diverse Traffic Patterns for Intrusion Detection—0
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations—0
Topological Data Analysis (TDA) Techniques Enhance Hand Pose Classification from ECoG Neural Recordings—0
To the Most Gracious Highness, from Your Humble Servant: Analysing Swedish 18th Century Petitions Using Text Classification—0
Towards a consistent interpretation of AIOps models—0
Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems using Feature Importance Fusion—0
Towards a Shapley Value Graph Framework for Medical peer-influence—0
Towards Auditing Large Language Models: Improving Text-based Stereotype Detection—0
Reconstructing Actions To Explain Deep Reinforcement Learning—0
Towards Global Explanations of Convolutional Neural Networks With Concept Attribution—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1VarImpVIANNPearson Correlation0.76—Unverified
2Garson Variable ImportancePearson 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