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GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
We present GluonCV and GluonNLP, the deep learning toolkits for computer...
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STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems
We propose a new STAcked and Reconstructed Graph Convolutional Networks ...
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Machine Learning for Spatiotemporal Sequence Forecasting: A Survey
Spatiotemporal systems are common in the real-world. Forecasting the mul...
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GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs
We propose a new network architecture, Gated Attention Networks (GaAN), ...
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Spatiotemporal Modeling for Crowd Counting in Videos
Region of Interest (ROI) crowd counting can be formulated as a regressio...
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Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model
With the goal of making high-resolution forecasts of regional rainfall, ...
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Dynamic Key-Value Memory Networks for Knowledge Tracing
Knowledge Tracing (KT) is a task of tracing evolving knowledge state of ...
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Collaborative Recurrent Autoencoder: Recommend while Learning to Fill in the Blanks
Hybrid methods that utilize both content and rating information are comm...
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Natural-Parameter Networks: A Class of Probabilistic Neural Networks
Neural networks (NN) have achieved state-of-the-art performance in vario...
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Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
The goal of precipitation nowcasting is to predict the future rainfall i...
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