How BLUE is the Sky? Estimating air qualities in Beijing during the Blue Sky Day period (2008–2012) by Bayesian Multi-task LSTM

The seven tools of causal inference, with reflections on machine learning

(2019) Judea Pearl   COMMUNICATIONS OF THE ACM

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

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

(2017) Xiang Li et al.   ENVIRONMENTAL POLLUTION

Statistical corruption in Beijing's air quality data has likely ended in 2012

(2016) Thomas Stoerk   ATMOSPHERIC ENVIRONMENT

Combining machine learning and propensity score weighting to estimate causal effects in multivalued treatments

(2016) Ariel Linden et al.   JOURNAL OF EVALUATION IN CLINICAL PRACTICE

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

Inconsistencies in air quality metrics: ‘Blue Sky’ days and PM10concentrations in Beijing

(2008) Steven Q Andrews   Environmental Research Letters

Manipulation of the running variable in the regression discontinuity design: A density test

(2007) Justin McCrary   JOURNAL OF ECONOMETRICS