Visual Interpretation of Recurrent Neural Network on Multi-dimensional Time-series Forecast
暂无分享,去创建一个
Wei Zeng | Huamin Qu | Yanhong Wu | Qiaomu Shen | Yuzhe Jiang | Alexis K H LAU | Anna Vianova | Huamin Qu | Qiaomu Shen | A. Lau | W. Zeng | Yuzhe Jiang | Yanhong Wu | Anna Vianova | Wei Zeng
[1] Scott Lundberg,et al. A Unified Approach to Interpreting Model Predictions , 2017, NIPS.
[2] Judith C. Chow,et al. Characteristics of carbonaceous aerosol in Pearl River Delta Region, China during 2001 winter period , 2003 .
[3] Joachim Diederich,et al. Survey and critique of techniques for extracting rules from trained artificial neural networks , 1995, Knowl. Based Syst..
[4] Alexis K.H. Lau,et al. Seasonal characteristics and regional transport of PM2.5 in Hong Kong , 2005 .
[5] Zhen Li,et al. Understanding Hidden Memories of Recurrent Neural Networks , 2017, 2017 IEEE Conference on Visual Analytics Science and Technology (VAST).
[6] Xinlei Chen,et al. Visualizing and Understanding Neural Models in NLP , 2015, NAACL.
[7] P. Rousseeuw. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .
[8] Xiaogang Wang,et al. Deeply learned face representations are sparse, selective, and robust , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[9] Hao Yang,et al. Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review , 2018, Neural Computation.
[10] Fei-Fei Li,et al. Visualizing and Understanding Recurrent Networks , 2015, ArXiv.
[11] Inderjit S. Dhillon,et al. Co-clustering documents and words using bipartite spectral graph partitioning , 2001, KDD '01.
[12] Jude W. Shavlik,et al. in Advances in Neural Information Processing , 1996 .
[13] Alexander M. Rush,et al. LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks , 2016, IEEE Transactions on Visualization and Computer Graphics.
[14] J. Friedman. Greedy function approximation: A gradient boosting machine. , 2001 .
[15] Sepp Hochreiter,et al. Untersuchungen zu dynamischen neuronalen Netzen , 1991 .
[16] Takio Murakami,et al. Winter Monsoonal Surges over East and Southeast Asia1 , 1979 .
[17] Alexander M. Rush,et al. Seq2seq-Vis: A Visual Debugging Tool for Sequence-to-Sequence Models , 2018, IEEE Transactions on Visualization and Computer Graphics.
[18] Elmar Eisemann,et al. Visual analysis of mass cytometry data by hierarchical stochastic neighbour embedding reveals rare cell types , 2017, Nature Communications.
[19] Dit-Yan Yeung,et al. Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.
[20] Zhen Li,et al. Towards Better Analysis of Deep Convolutional Neural Networks , 2016, IEEE Transactions on Visualization and Computer Graphics.
[21] Ming Li,et al. Forecasting Fine-Grained Air Quality Based on Big Data , 2015, KDD.
[22] Jimeng Sun,et al. RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records , 2018, IEEE Transactions on Visualization and Computer Graphics.
[23] Zachary C. Lipton,et al. The Doctor Just Won't Accept That! , 2017, 1711.08037.
[24] Elmar Eisemann,et al. Hierarchical Stochastic Neighbor Embedding , 2016, Comput. Graph. Forum.
[25] Carlos Guestrin,et al. "Why Should I Trust You?": Explaining the Predictions of Any Classifier , 2016, ArXiv.
[26] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[27] Kuldip K. Paliwal,et al. Bidirectional recurrent neural networks , 1997, IEEE Trans. Signal Process..
[28] Elmar Eisemann,et al. DeepEyes: Progressive Visual Analytics for Designing Deep Neural Networks , 2018, IEEE Transactions on Visualization and Computer Graphics.
[29] Mihaela Oprea,et al. A neural network based model for PM2.5 air pollutant forecasting , 2016, 2016 20th International Conference on System Theory, Control and Computing (ICSTCC).
[30] Jürgen Schmidhuber,et al. Applying LSTM to Time Series Predictable through Time-Window Approaches , 2000, ICANN.
[31] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.