conftrace_
← Core AI
Artificial Intelligence › Core AI ›

Interpretability

7,318 papers

Papers per year

Papers

Can Information Flows Suggest Targets for Interventions in Neural Circuits? NIPS 2021
From global to local MDI variable importances for random forests and when they are Shapley values NIPS 2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations NIPS 2021
Neural Additive Models: Interpretable Machine Learning with Neural Nets NIPS 2021
Overcoming the Convex Barrier for Simplex Inputs NIPS 2021
Robust Counterfactual Explanations on Graph Neural Networks NIPS 2021
On Success and Simplicity: A Second Look at Transferable Targeted Attacks NIPS 2021
Provably efficient, succinct, and precise explanations NIPS 2021
Exploring the Limits of Out-of-Distribution Detection NIPS 2021
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift NIPS 2021
Locally Valid and Discriminative Prediction Intervals for Deep Learning Models NIPS 2021
Interpreting Representation Quality of DNNs for 3D Point Cloud Processing NIPS 2021
Generalizable Multi-linear Attention Network NIPS 2021
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability NIPS 2021
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification NIPS 2021
Causal Abstractions of Neural Networks NIPS 2021
Co-Adaptation of Algorithmic and Implementational Innovations in Inference-based Deep Reinforcement Learning NIPS 2021
Controlling Neural Networks with Rule Representations NIPS 2021
Foundations of Symbolic Languages for Model Interpretability NIPS 2021
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? NIPS 2021
Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence NIPS 2021
EDGE: Explaining Deep Reinforcement Learning Policies NIPS 2021
Understanding Interlocking Dynamics of Cooperative Rationalization NIPS 2021
Adversarial Robustness without Adversarial Training: A Teacher-Guided Curriculum Learning Approach NIPS 2021
A universal probabilistic spike count model reveals ongoing modulation of neural variability NIPS 2021