887 citations · 1k across the 3 of their papers we have counts for
5 papers
Predicting Economic Development using Geolocated Wikipedia Articles
Evan Sheehan, Chenlin Meng, Matthew Tan +5
Progress on the UN Sustainable Development Goals (SDGs) is hampered by a persistent lack of data regarding key social, environmental, and economic indicators, particularly in devel…
Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning
Chi-Sing Ho, Neal Jean, Catherine A. Hogan +7
Rapid identification of bacteria is essential to prevent the spread of infectious disease, help combat antimicrobial resistance, and improve patient outcomes. Raman optical spectro…
Tile2Vec: Unsupervised representation learning for spatially distributed data
Neal Jean, Sherrie Wang, Anshul Samar +3
Geospatial analysis lacks methods like the word vector representations and pre-trained networks that significantly boost performance across a wide range of natural language and com…
Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
Neal Jean, Sang Michael Xie, Stefano Ermon
Large amounts of labeled data are typically required to train deep learning models. For many real-world problems, however, acquiring additional data can be expensive or even imposs…
Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping
Michael Xie, Neal Jean, Marshall Burke +2
The lack of reliable data in developing countries is a major obstacle to sustainable development, food security, and disaster relief. Poverty data, for example, is typically scarce…