conftrace_
← Core AI
Artificial Intelligence › Core AI ›

Interpretability

7,452 papers

Papers per year

5
14
488
1716
'10
'15
'20
'25

Papers

Sampling-Free Epistemic Uncertainty Estimation Using Approximated Variance Propagation ICCV 2019
Understanding Deep Networks via Extremal Perturbations and Smooth Masks ICCV 2019
Dynamic Graph Attention for Referring Expression Comprehension ICCV 2019
Hilbert-Based Generative Defense for Adversarial Examples ICCV 2019
Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks ICCV 2019
XRAI: Better Attributions Through Regions ICCV 2019
GANalyze: Toward Visual Definitions of Cognitive Image Properties ICCV 2019
Towards Interpretable Object Detection by Unfolding Latent Structures ICCV 2019
U-CAM: Visual Explanation Using Uncertainty Based Class Activation Maps ICCV 2019
DenseRaC: Joint 3D Pose and Shape Estimation by Dense Render-and-Compare ICCV 2019
Explaining Neural Networks Semantically and Quantitatively ICCV 2019
Towards Interpretable Face Recognition ICCV 2019
Mixture-Kernel Graph Attention Network for Situation Recognition ICCV 2019
Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks ICLR 2019
Fairwashing: the risk of rationalization ICML 2019
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation ICML 2019
What is the Effect of Importance Weighting in Deep Learning? ICML 2019
Neural Network Attributions: A Causal Perspective ICML 2019
On the Connection Between Adversarial Robustness and Saliency Map Interpretability ICML 2019
Counterfactual Visual Explanations ICML 2019
Towards a Deep and Unified Understanding of Deep Neural Models in NLP ICML 2019
Exploring interpretable LSTM neural networks over multi-variable data ICML 2019
Neural Logic Reinforcement Learning ICML 2019
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models ICML 2019
Homomorphic Sensing ICML 2019