SOTAVerified

Interpretability Techniques for Deep Learning

Papers

Showing 1120 of 25 papers

TitleStatusHype
A Novel Deep Learning Model for Hotel Demand and Revenue Prediction amid COVID-19Code1
A Semi-supervised Deep Transfer Learning Approach for Rolling-Element Bearing Remaining Useful Life PredictionCode0
DISSECT: Disentangled Simultaneous Explanations via Concept TraversalsCode1
A deep supervised learning approach for condition-based maintenance of naval propulsion systems Tarek0
DeepNNK: Explaining deep models and their generalization using polytope interpolationCode0
Exploration of Interpretability Techniques for Deep COVID-19 Classification using Chest X-ray ImagesCode1
An Investigation of Interpretability Techniques for Deep Learning in Predictive Process Analytics0
What Do Compressed Deep Neural Networks Forget?Code0
RISE: Randomized Input Sampling for Explanation of Black-box ModelsCode1
Contextual Explanation NetworksCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DASLog odds-ratio (pythia-6.9b)9.95Unverified
2Linear probeLog odds-ratio (pythia-6.9b)3.42Unverified
3Difference-in-meansLog odds-ratio (pythia-6.9b)2.91Unverified
4k-meansLog odds-ratio (pythia-6.9b)1.87Unverified
5PCALog odds-ratio (pythia-6.9b)1.81Unverified
6LDALog odds-ratio (pythia-6.9b)0.27Unverified
7RandomLog odds-ratio (pythia-6.9b)0.01Unverified
#ModelMetricClaimedVerifiedStatus
1RISEInsertion AUC score0.57Unverified
2HSIC-AttributionInsertion AUC score0.57Unverified
3Kernel SHAPInsertion AUC score0.52Unverified
4LIMEInsertion AUC score0.52Unverified
5SaliencyInsertion AUC score0.46Unverified
6Grad-CAMInsertion AUC score0.37Unverified
7Integrated GradientsInsertion AUC score0.36Unverified