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Artificial Intelligence
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Core AI
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Interpretability
7,318 papers
Papers per year
2003: 1
2006: 1
2007: 1
2008: 1
2009: 1
2010: 5
2012: 2
2013: 10
2014: 7
2015: 14
2016: 27
2017: 84
2018: 196
2019: 395
2020: 488
2021: 771
2022: 823
2023: 954
2024: 1360
2025: 1713
2026: 464
Papers
Robust Bayesian recourse
UAI 2022
Attribution of predictive uncertainties in classification models
UAI 2022
F-CAM: Full Resolution Class Activation Maps via Guided Parametric Upscaling
WACV 2022
X-MIR: EXplainable Medical Image Retrieval
WACV 2022
Attack Agnostic Detection of Adversarial Examples via Random Subspace Analysis
WACV 2022
Agree To Disagree: When Deep Learning Models With Identical Architectures Produce Distinct Explanations
WACV 2022
Semantically Stealthy Adversarial Attacks Against Segmentation Models
WACV 2022
HHP-Net: A Light Heteroscedastic Neural Network for Head Pose Estimation With Uncertainty
WACV 2022
Non-Semantic Evaluation of Image Forensics Tools: Methodology and Database
WACV 2022
SWAG-V: Explanations for Video Using Superpixels Weighted by Average Gradients
WACV 2022
Non-Local Attention Improves Description Generation for Retinal Images
WACV 2022
Surrogate Model-Based Explainability Methods for Point Cloud NNs
WACV 2022
How Good Is Your Explanation? Algorithmic Stability Measures To Assess the Quality of Explanations for Deep Neural Networks
WACV 2022
Interpretable Semantic Photo Geolocation
WACV 2022
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution
NIPS 2021
ReAct: Out-of-distribution Detection With Rectified Activations
NIPS 2021
CentripetalText: An Efficient Text Instance Representation for Scene Text Detection
NIPS 2021
Local Explanation of Dialogue Response Generation
NIPS 2021
The Utility of Explainable AI in Ad Hoc Human-Machine Teaming
NIPS 2021
On the Importance of Gradients for Detecting Distributional Shifts in the Wild
NIPS 2021
Towards robust vision by multi-task learning on monkey visual cortex
NIPS 2021
Single Layer Predictive Normalized Maximum Likelihood for Out-of-Distribution Detection
NIPS 2021
Explaining Hyperparameter Optimization via Partial Dependence Plots
NIPS 2021
Understanding Instance-based Interpretability of Variational Auto-Encoders
NIPS 2021
On Model Calibration for Long-Tailed Object Detection and Instance Segmentation
NIPS 2021
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