neural network interpretability

Neural Network Attributions: A Causal Perspective ICML 2019 Relating Simple Sentence Representations in Deep Neural Networks and the Brain ACL 2019 Robust Attribution Regularization NeurIPS 2019 This Looks Like That: Deep Learning for Interpretable Image Recognition NeurIPS 2019 Towards Automatic Concept-based Explanations NeurIPS 2019 What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Neurons EMNLP 2019 Automatic Gating of Attributes in Deep Structure IJCAI 2018 Evaluating neural network explanation methods using hybrid documents and morphosyntactic agreement ACL 2018 Exploring How Phone Classification Neural Networks Learn Phonetic Information by Visualising and Interpreting Bottleneck Features Interspeech 2018 Interpreting Neural Network Judgments via Minimal, Stable, and Symbolic Corrections NeurIPS 2018 Interpret Neural Networks by Identifying Critical Data Routing Paths CVPR 2018 Learning how to explain neural networks: PatternNet and PatternAttribution ICLR 2018 Neural Interaction Transparency (NIT): Disentangling Learned Interactions for Improved Interpretability NeurIPS 2018 Pathologies of Neural Models Make Interpretations Difficult EMNLP 2018 Towards better understanding of gradient-based attribution methods for Deep Neural Networks ICLR 2018 Gate Activation Signal Analysis for Gated Recurrent Neural Networks and its Correlation with Phoneme Boundaries Interspeech 2017 Revisit Fuzzy Neural Network: Demystifying Batch Normalization and ReLU with Generalized Hamming Network NeurIPS 2017 Synthesizing the preferred inputs for neurons in neural networks via deep generator networks NeurIPS 2016