Mengnan Du

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Texas A&M University

Score-CAM:Improved Visual Explanations Via Score-Weighted Class Activation Mapping

Recently, more and more attention has been drawn into the internal mecha...
10/03/2019 ∙ by Haofan Wang, et al. ∙ 25 ∙ share

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Deep Structured Cross-Modal Anomaly Detection

Anomaly detection is a fundamental problem in data mining field with man...
08/11/2019 ∙ by Yuening Li, et al. ∙ 8 ∙ share

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Evaluating Explanation Without Ground Truth in Interpretable Machine Learning

Interpretable Machine Learning (IML) has become increasingly important i...
07/16/2019 ∙ by Fan Yang, et al. ∙ 7 ∙ share

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Towards Explanation of DNN-based Prediction with Guided Feature Inversion

While deep neural networks (DNN) have become an effective computational ...
03/19/2018 ∙ by Mengnan Du, et al. ∙ 0 ∙ share

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Techniques for Interpretable Machine Learning

Interpretable machine learning tackles the important problem that humans...
07/31/2018 ∙ by Mengnan Du, et al. ∙ 0 ∙ share

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On Attribution of Recurrent Neural Network Predictions via Additive Decomposition

RNN models have achieved the state-of-the-art performance in a wide rang...
03/27/2019 ∙ by Mengnan Du, et al. ∙ 0 ∙ share

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SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

Anomaly detection aims to distinguish observations that are rare and dif...
08/11/2019 ∙ by Yuening Li, et al. ∙ 0 ∙ share

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XFake: Explainable Fake News Detector with Visualizations

In this demo paper, we present the XFake system, an explainable fake new...
07/08/2019 ∙ by Fan Yang, et al. ∙ 0 ∙ share

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Towards Generalizable Forgery Detection with Locality-aware AutoEncoder

With advancements of deep learning techniques, it is now possible to gen...
09/13/2019 ∙ by Mengnan Du, et al. ∙ 0 ∙ share

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Learning Credible Deep Neural Networks with Rationale Regularization

Recent explainability related studies have shown that state-of-the-art D...
08/13/2019 ∙ by Mengnan Du, et al. ∙ 0 ∙ share

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Fairness in Deep Learning: A Computational Perspective

Deep learning is increasingly being used in high-stake decision making a...
08/23/2019 ∙ by Mengnan Du, et al. ∙ 0 ∙ share

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Sub-Architecture Ensemble Pruning in Neural Architecture Search

Neural architecture search (NAS) is gaining more and more attention in r...
10/01/2019 ∙ by Yijun Bian, et al. ∙ 0 ∙ share

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Mengnan Du

Featured Co-authors

Fan Yang

Xia Hu

Shuiwang Ji

Xiao Huang

Huanhuan Chen

Sina Mohseni

Jundong Li

Qingquan Song

Zijian Zhang

Ninghao Liu

Yuening Li

Score-CAM:Improved Visual Explanations Via Score-Weighted Class Activation Mapping

Deep Structured Cross-Modal Anomaly Detection

Evaluating Explanation Without Ground Truth in Interpretable Machine Learning

Towards Explanation of DNN-based Prediction with Guided Feature Inversion

Techniques for Interpretable Machine Learning

On Attribution of Recurrent Neural Network Predictions via Additive Decomposition

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks

XFake: Explainable Fake News Detector with Visualizations

Towards Generalizable Forgery Detection with Locality-aware AutoEncoder

Learning Credible Deep Neural Networks with Rationale Regularization

Fairness in Deep Learning: A Computational Perspective

Sub-Architecture Ensemble Pruning in Neural Architecture Search