Extracting spatial effects from machine learning model using local interpretation method: An example of SHAP and XGBoost

A machine learning approach for modelling parking duration in urban land-use

(2021) Janak Parmar et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

Knowledge-Driven GeoAI: Integrating Spatial Knowledge into Multi-Scale Deep Learning for Mars Crater Detection

(2021) Chia-Yu Hsu et al.   Remote Sensing

Are We Modelling Spatially Varying Processes or Non‐linear Relationships?

(2021) Mehak Sachdeva et al.   GEOGRAPHICAL ANALYSIS

The PySAL Ecosystem: Philosophy and Implementation

(2021) Sergio J. Rey et al.   GEOGRAPHICAL ANALYSIS

Evaluation of the factors explaining the use of agricultural land: A machine learning and model-agnostic approach

(2021) Cláudia M. Viana et al.   ECOLOGICAL INDICATORS

Tabular data: Deep learning is not all you need

(2021) Ravid Shwartz-Ziv et al.   Information Fusion

Geographically neural network weighted regression for the accurate estimation of spatial non-stationarity

(2020) Zhenhong Du et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

Computational improvements to multi-scale geographically weighted regression

(2020) Ziqi Li et al.   INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE

Advancing methodologies for applying machine learning and evaluating spatiotemporal models of fine particulate matter (PM2.5) using satellite data over large regions

(2020) Allan C. Just et al.   ATMOSPHERIC ENVIRONMENT

Mapping the landscape of Artificial Intelligence applications against COVID-19

(2020) Joseph Bullock et al.   JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH

Interpretable vs. noninterpretable machine learning models for data-driven hydro-climatological process modeling

(2020) Debaditya Chakraborty et al.   EXPERT SYSTEMS WITH APPLICATIONS

DARPA’s Explainable Artificial Intelligence (XAI) Program

(2019) David Gunning et al.   AI MAGAZINE

Social sensing from street-level imagery: A case study in learning spatio-temporal urban mobility patterns

(2019) Fan Zhang et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

PM2.5 Prediction Based on Random Forest, XGBoost, and Deep Learning Using Multisource Remote Sensing Data

(2019) Mehdi Zamani Joharestani et al.   Atmosphere

MGWR: A Python Implementation of Multiscale Geographically Weighted Regression for Investigating Process Spatial Heterogeneity and Scale

(2019) Taylor M. Oshan et al.   ISPRS International Journal of Geo-Information

Land-cover classification with high-resolution remote sensing images using transferable deep models

(2019) Xin-Yi Tong et al.   REMOTE SENSING OF ENVIRONMENT

Points of Significance: Statistics versus machine learning

(2018) Danilo Bzdok et al.   NATURE METHODS

Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study

(2018) Shane Nanayakkara et al.   PLOS MEDICINE

Training Deep Convolutional Neural Networks for Land–Cover Classification of High-Resolution Imagery

(2017) Grant J. Scott et al.   IEEE Geoscience and Remote Sensing Letters

A gradient boosting method to improve travel time prediction

(2015) Yanru Zhang et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Explaining prediction models and individual predictions with feature contributions

(2013) Erik Štrumbelj et al.   KNOWLEDGE AND INFORMATION SYSTEMS

Classification with correlated features: unreliability of feature ranking and solutions

(2011) Laura Toloşi et al.   BIOINFORMATICS

The Use of Geographically Weighted Regression for Spatial Prediction: An Evaluation of Models Using Simulated Data Sets

(2010) P. Harris et al.   Mathematical Geosciences

Surveillance Sans Frontières: Internet-Based Emerging Infectious Disease Intelligence and the HealthMap Project

(2008) John S Brownstein et al.   PLOS MEDICINE