A Domain-Specific Bayesian Deep-Learning Approach for Air Pollution Forecast

Deep learning PM2.5 concentrations with bidirectional LSTM RNN

(2019) Weitian Tong et al.   Air Quality Atmosphere and Health

Deep learning and process understanding for data-driven Earth system science

(2019) Markus Reichstein et al.   NATURE

A hybrid model for spatiotemporal forecasting of PM2.5 based on graph convolutional neural network and long short-term memory

(2019) Yanlin Qi et al.   SCIENCE OF THE TOTAL ENVIRONMENT

A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide

(2019) Jie Chen et al.   ENVIRONMENT INTERNATIONAL

Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-grained Air Quality

(2018) Zhongang Qi et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

A review of air pollution impact on subjective well-being: Survey versus visual psychophysics

(2018) Yuan Li et al.   JOURNAL OF CLEANER PRODUCTION

A Deep CNN-LSTM Model for Particulate Matter (PM2.5) Forecasting in Smart Cities

(2018) Chiou-Jye Huang et al.   SENSORS

Forecasting air quality time series using deep learning

(2018) Brian S. Freeman et al.   JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION

Air Pollution Forecasts: An Overview

(2018) Lu Bai et al.   International Journal of Environmental Research and Public Health

Comparison of Ground-Based PM2.5 and PM10 Concentrations in China, India, and the U.S.

(2018) Xingchuan Yang et al.   International Journal of Environmental Research and Public Health

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Explore a deep learning multi-output neural network for regional multi-step-ahead air quality forecasts

(2018) Yanlai Zhou et al.   JOURNAL OF CLEANER PRODUCTION

Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning

(2018) Changde Du et al.   IEEE Transactions on Neural Networks and Learning Systems

Long short-term memory neural network for air pollutant concentration predictions: Method development and evaluation

(2017) Xiang Li et al.   ENVIRONMENTAL POLLUTION

The “APEC blue” endeavor: Causal effects of air pollution regulation on air quality in China

(2017) Xiao Li et al.   JOURNAL OF CLEANER PRODUCTION

Particulate matter pollution over China and the effects of control policies

(2017) Jiandong Wang et al.   SCIENCE OF THE TOTAL ENVIRONMENT

Towards Bayesian Deep Learning: A Framework and Some Existing Methods

(2016) Hao Wang et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Deep learning

(2015) Yann LeCun et al.   NATURE

Dynamically pre-trained deep recurrent neural networks using environmental monitoring data for predicting PM2.5

(2015) Bun Theang Ong et al.   NEURAL COMPUTING & APPLICATIONS

PM 2.5 in China: Measurements, sources, visibility and health effects, and mitigation

(2014) David Y.H. Pui et al.   Particuology

Estimation of Citywide Air Pollution in Beijing

(2013) Jin-Feng Wang et al.   PLoS One

Understanding of regional air pollution over China using CMAQ, part I performance evaluation and seasonal variation

(2010) Xiao-Huan Liu et al.   ATMOSPHERIC ENVIRONMENT

The Bayesian Lasso

(2008) Trevor Park et al.   JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION