On the opportunities and challenges of foundation models for geospatial artificial intelligence

G Mai, W Huang, J Sun, S Song, D Mishra… - arXiv preprint arXiv …, 2023 - arxiv.org
Large pre-trained models, also known as foundation models (FMs), are trained in a task-
agnostic manner on large-scale data and can be adapted to a wide range of downstream …

Csp: Self-supervised contrastive spatial pre-training for geospatial-visual representations

G Mai, N Lao, Y He, J Song… - … Conference on Machine …, 2023 - proceedings.mlr.press
Geo-tagged images are publicly available in large quantities, whereas labels such as object
classes are rather scarce and expensive to collect. Meanwhile, contrastive learning has …

Sphere2Vec: A general-purpose location representation learning over a spherical surface for large-scale geospatial predictions

G Mai, Y Xuan, W Zuo, Y He, J Song, S Ermon… - ISPRS Journal of …, 2023 - Elsevier
Generating learning-friendly representations for points in space is a fundamental and long-
standing problem in machine learning. Recently, multi-scale encoding schemes (such as …

A five-year milestone: reflections on advances and limitations in GeoAI research

Y Hu, M Goodchild, AX Zhu, M Yuan, O Aydin… - Annals of …, 2024 - Taylor & Francis
ABSTRACT The Annual Meeting of the American Association of Geographers (AAG) in 2023
marked a five-year milestone since the first Geospatial Artificial Intelligence (GeoAI) …

AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology

H Dai, Y Li, Z Liu, L Zhao, Z Wu, S Song, Y Shen… - arXiv preprint arXiv …, 2023 - arxiv.org
In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application
based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT …

Exploring new frontiers in agricultural nlp: Investigating the potential of large language models for food applications

S Rezayi, Z Liu, Z Wu, C Dhakal, B Ge, H Dai… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper explores new frontiers in agricultural natural language processing by
investigating the effectiveness of using food-related text corpora for pretraining transformer …

Explainable spatially explicit geospatial artificial intelligence in urban analytics

P Liu, Y Zhang, F Biljecki - Environment and Planning B …, 2024 - journals.sagepub.com
Geospatial artificial intelligence (GeoAI) is proliferating in urban analytics, where graph
neural networks (GNNs) have become one of the most popular methods in recent years …

CATS: Conditional Adversarial Trajectory Synthesis for privacy-preserving trajectory data publication using deep learning approaches

J Rao, S Gao, S Zhu - International Journal of Geographical …, 2023 - Taylor & Francis
The prevalence of ubiquitous location-aware devices and mobile Internet enables us to
collect massive individual-level trajectory dataset from users. Such trajectory big data bring …

EVKG: An interlinked and interoperable electric vehicle knowledge graph for smart transportation system

Y Qi, G Mai, R Zhu, M Zhang - Transactions in GIS, 2023 - Wiley Online Library
Over the past decade, the electric vehicle (EV) industry has experienced unprecedented
growth and diversification, resulting in a complex ecosystem. To effectively manage this …

GeoAI in urban analytics

S De Sabbata, A Ballatore, HJ Miller… - International Journal …, 2023 - Taylor & Francis
We are writing this editorial piece at the peak of the current Artificial Intelligence
(AI)'spring'as generative models quickly cross the bridge from the confines of academic and …