awesome_deep_learning_interpretability

深度学习近年来关于模型解释性的相关论文。

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159篇论文pdf(有2篇需要上scihub找)上传到腾讯微云。

不定期更新。

Year	Publication	Paper	Citation	code
2020	CVPR	Explaining Knowledge Distillation by Quantifying the Knowledge	81
2020	CVPR	High-frequency Component Helps Explain the Generalization of Convolutional Neural Networks	289
2020	CVPRW	Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks	414	Pytorch
2020	ICLR	Knowledge consistency between neural networks and beyond	28
2020	ICLR	Interpretable Complex-Valued Neural Networks for Privacy Protection	23
2019	AI	Explanation in artificial intelligence: Insights from the social sciences	3248
2019	NMI	Stop Explaining Black Box Machine Learning Models for High Stakes Decisions and Use Interpretable Models Instead	3505
2019	NeurIPS	Can you trust your model's uncertainty? Evaluating predictive uncertainty under dataset shift	1052	-
2019	NeurIPS	This looks like that: deep learning for interpretable image recognition	665	Pytorch
2019	NeurIPS	A benchmark for interpretability methods in deep neural networks	413
2019	NeurIPS	Full-gradient representation for neural network visualization	155
2019	NeurIPS	On the (In) fidelity and Sensitivity of Explanations	226
2019	NeurIPS	Towards Automatic Concept-based Explanations	342	Tensorflow
2019	NeurIPS	CXPlain: Causal explanations for model interpretation under uncertainty	133
2019	CVPR	Interpreting CNNs via Decision Trees	293
2019	CVPR	From Recognition to Cognition: Visual Commonsense Reasoning	544	Pytorch
2019	CVPR	Attention branch network: Learning of attention mechanism for visual explanation	371
2019	CVPR	Interpretable and fine-grained visual explanations for convolutional neural networks	116
2019	CVPR	Learning to Explain with Complemental Examples	36
2019	CVPR	Revealing Scenes by Inverting Structure from Motion Reconstructions	84	Tensorflow
2019	CVPR	Multimodal Explanations by Predicting Counterfactuality in Videos	26
2019	CVPR	Visualizing the Resilience of Deep Convolutional Network Interpretations	2
2019	ICCV	U-CAM: Visual Explanation using Uncertainty based Class Activation Maps	61
2019	ICCV	Towards Interpretable Face Recognition	66
2019	ICCV	Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded	163
2019	ICCV	Understanding Deep Networks via Extremal Perturbations and Smooth Masks	276	Pytorch
2019	ICCV	Explaining Neural Networks Semantically and Quantitatively	49
2019	ICLR	Hierarchical interpretations for neural network predictions	111	Pytorch
2019	ICLR	How Important Is a Neuron?	101
2019	ICLR	Visual Explanation by Interpretation: Improving Visual Feedback Capabilities of Deep Neural Networks	56
2018	ICML	Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples	169	Pytorch
2019	ICML	Towards A Deep and Unified Understanding of Deep Neural Models in NLP	80	Pytorch
2019	ICAIS	Interpreting black box predictions using fisher kernels	80
2019	ACMFAT	Explaining explanations in AI	558
2019	AAAI	Interpretation of neural networks is fragile	597	Tensorflow
2019	AAAI	Classifier-agnostic saliency map extraction	23
2019	AAAI	Can You Explain That? Lucid Explanations Help Human-AI Collaborative Image Retrieval	11
2019	AAAIW	Unsupervised Learning of Neural Networks to Explain Neural Networks	28
2019	AAAIW	Network Transplanting	4
2019	CSUR	A Survey of Methods for Explaining Black Box Models	3088
2019	JVCIR	Interpretable convolutional neural networks via feedforward design	134	Keras
2019	ExplainAI	The (Un)reliability of saliency methods	515
2019	ACL	Attention is not Explanation	920
2019	EMNLP	Attention is not not Explanation	667
2019	arxiv	Attention Interpretability Across NLP Tasks	129
2019	arxiv	Interpretable CNNs	2
2018	ICLR	Towards better understanding of gradient-based attribution methods for deep neural networks	775
2018	ICLR	Learning how to explain neural networks: PatternNet and PatternAttribution	342
2018	ICLR	On the importance of single directions for generalization	282	Pytorch
2018	ICLR	Detecting statistical interactions from neural network weights	148	Pytorch
2018	ICLR	Interpretable counting for visual question answering	55	Pytorch
2018	CVPR	Interpretable Convolutional Neural Networks	677
2018	CVPR	Tell me where to look: Guided attention inference network	454	Chainer
2018	CVPR	[Multimodal Explanations: Justifying Decisions and Pointing to the