Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper
Query: A Deep Learning Approach for Air Pollution Forecasting in South Korea Using Encoder-Decoder Networks & LSTM.
Deep Air : Forecasting Air Pollution in Beijing , China
Weather forecasting using deep learning techniques
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Air pollution monitoring and prediction using IoT
Load forecasting using deep neural networks
Multiple adaptive kernel size KLMS for Beijing PM2.5 prediction
Graph-Based Deep Modeling and Real Time Forecasting of Sparse Spatio-Temporal Data
Deep State Space Models for Time Series Forecasting
Deep Learning: A Generic Approach for Extreme Condition Traffic Forecasting
Applications of Recurrent Neural Networks in Environmental Factor Forecasting: A Review
U-Air: when urban air quality inference meets big data
Ensemble of Deep Neural Networks for Estimating Particulate Matter from Images
Improving Long-Horizon Forecasts with Expectation-Biased LSTM Networks
A Deep-Learning Based Precipitation Forecasting Approach Using Multiple Environmental Factors
IOT-based air pollution monitoring and forecasting system
Towards Air Quality Estimation Using Collected Multimodal Environmental Data
Accurate photovoltaic power forecasting models using deep LSTM-RNN
A CFCC-LSTM Model for Sea Surface Temperature Prediction
Deep Sequence Learning with Auxiliary Information for Traffic Prediction
Deep neural networks for time series prediction with applications in ultra-short-term wind forecasting
Gradient-Based Learning Algorithms for Recurrent Networks and Their Computational Complexity
Selection of the number of clusters via the bootstrap method
LESCs: Lateralizing Eyelid Sleep Compression Study.
Slice-timing effects and their correction in functional MRI
Taking Human out of Learning Applications: A Survey on Automated Machine Learning