We have a class associated with the lab: CS325b

Selected publications

  • Yezhen Cong, Samar Khanna, Chenlin Meng, Patrick Liu, Erik Rozi, Yutong He, Marshall Burke, David Lobell, Stefano Ermon.
    SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery.
    In Proc. 36th Annual Conference on Neural Information Processing Systems (NeurIPS 2022).

  • Chenlin Meng, Enci Liu, Willie Neiswanger, Jiaming Song, Marshall Burke, David Lobell, Stefano Ermon.
    IS-Count: Large-scale Object Counting from Satellite Images with Covariate-based Importance Sampling.
    In Proc. 36th AAAI Conference on Artificial Intelligence (AAAI 2022).

  • Christopher Yeh, Chenlin Meng, Sherrie Wang, Anne Driscoll, Erik Rozi, Patrick Liu, Jihyeon Lee, Marshall Burke, David B. Lobell, Stefano Ermon. SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning. To appear, NeurIPS ‘21

  • Yutong He, Dingjie Wang, Nicholas Lai, William Zhang, Chenlin Meng, Marshall Burke, David B. Lobell, Stefano Ermon. "Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis". 2021 [Arxiv] To appear, NeurIPS ‘21

  • Jihyeon Lee, Nina Brooks, Fahim Tajwar, Marshall Burke, Stefano Ermon, David Lobell, Debashish Biswas, and Steve Luby. 2021. Scalable deep learning to identify brick kilns and aid regulatory capacityPNAS 118(17), 2021[replication data]

  • Marshall Burke, Anne Driscoll, David Lobell, and Stefano Ermon. 2021. Using satellite imagery to understand and promote sustainable development. Science 371(6535). [replication data]

  • Jihyeon Janel Lee, Dylan Grosz, Sicheng Zheng, Burak Uzkent, Marshall Burke, David Lobell, Stefano Ermon. “Predicting Livelihood Indicators from Crowdsourced Street Level Images”. [arxiv] AAAI-21

  • Kumar Ayush, Burak Uzkent, Marshall Burke, David Lobell, Stefano Ermon. “Efficient Poverty Mapping using Deep Reinforcement Learning”. [arxiv] AAAI-21

  • Chris Yeh, Anthony Perez, George Azzari, Anne Driscoll, Zhongyi Tang, David Lobell, Stefano Ermon, and Marshall Burke. 2020. Using publicly available satellite imagery and deep learning to understand economic wellbeing in AfricaNature Communications 2020(11), 2583. 

  • Marc Rußwurm, Sherrie Wang, Marco Körner, David Lobell. 2020. “Meta-Learning for Few-Shot Land Cover Classification”. CVPR ‘20 [PDF]

  • K. Ayush, B. Uzkent, M. Burke, D. Lobell, S. Ermon, “Generating Interpretable Poverty Maps Using Object Detection in Satellite Images”, In Proceedings of International Joint Conference on Artificial Intelligence, August 2020 [PDF]

  • Sherrie Wang, William Chen, Sang Michael Xie, George Azzari, David Lobell. 2020. Weakly supervised deep learning for segmentation of remote sensing imagery, Remote Sensing. [code]

  • B. Uzkent, S. Ermon, “Learning When and Where to Zoom Using Deep Reinforcement Learning”, In Proceedings of IEEE Computer Vision and Pattern Recognition, July 2020 [PDF]

  • V. Sarukkai, A. Jain, B. Uzkent, S. Ermon, “Cloud Removal from Satellite Images Using Spatiotemporal Generator Networks”, In Proceedings of IEEE Winter Conference of Applications of Computer Vision (WACV), March 2020 [PDF]

  • B. Uzkent, C. Yeh, S. Ermon, “Efficient Object Detection in Large Images Using Deep Reinforcement Learning”, In Proceedings of IEEE Winter Conference of Applications of Computer Vision (WACV), March 2020 [PDF]

  • Rose Rustowicz, Robin Cheong, Lijing Wang, Stefano Ermon, Marshall Burke, and David Lobell. 2019. "Semantic segmentation of crop type in Africa: A novel dataset and analysis of deep learning methods", CVPR '19.

  • Burak Uzkent, Evan Sheehan, Chenlin Meng, Zhongyi Tang, David Lobell, Marshall Burke, Stefano Ermon
    ”Learning to Interpret Satellite Images using Wikipedia” [PDF]. IJCAI-19. To appear in Proc. 28th International Joint Conference on Artificial Intelligence, 2019.

  • Evan Sheehan, Chenlin Meng, Matthew Tan, Burak Uzkent, Neal Jean, David Lobell, Marshall Burke, Stefano Ermon. “Predicting Economic Development using Geolocated Wikipedia Articles” [PDF]. KDD-19. To appear in Proc. 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2019.

  • Wenjie Hu, Jay Harshadbhai Patel, Zoe-Alanah Robert, Paul Novosad, Samuel Asher, Zhongyi Tang, Marshall Burke, David Lobell, Stefano Ermon. 2019. “Mapping Missing Population in Rural India: A Deep Learning Approach with Satellite Imagery”. To appear in Proc. 1st AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES 2019). [PDF]

  • Sherrie Wang, George Azzari, David Lobell. 2019. “Crop type mapping without field-level labels: Random forest transfer and unsupervised clustering techniques.” Remote Sensing of Environment, 222, 303-317

  • Neal Jean, Sherrie Wang, Anshul Samar, George Azzari, David Lobell, Stefano Ermon
    Tile2Vec: Unsupervised representation learning for spatially distributed data [PDF] AAAI-19. To appear in Proc. 33rd AAAI Conference on Artificial Intelligence, 2019.

  • Barak Oshri, Annie Hu, Peter Adelson, Xiao Chen, Pascaline Dupas, Jeremy Weinstein, Marshall Burke, David Lobell, Stefano Ermon. 2018. "Infrastructure Quality Assessment in Africa using Satellite Imagery and Deep Learning". Proc. 24th ACM SIGKDD Conference, 2018.

  • Anthony Perez, Chris Yeh, George Azzari, Marshall Burke, David Lobell, Stefano Ermon. 2017. “Poverty Prediction with Public Landsat 7 Satellite Imagery and Machine Learning”, 31st Conference on Neural Information Processing Systems (NIPS 2017) [PDF]

  • Jiaxuan You, Xiaocheng Li, Melvin Low, David Lobell, Stefano Ermon
    Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data [PDF] [Code] AAAI-17. In Proc. 31st AAAI Conference on Artificial Intelligence, February 2017.

  • Marshall Burke and David Lobell. 2017. “Satellite-based assessment of yield variation and its determinants in smallholder African systems.” PNAS 114, 9.

    • Related crop yield work here

  • Neal Jean, Marshall Burke, MIchael Xie, W. Matt Davis, David Lobell, and Stefano Ermon. 2016. “Combining satellite imagery and machine learning to predict poverty.Science 353, 6301.

  • Michael Xie, Neal Jean, Marshall Burke, David Lobell, Stefano Ermon
    Transfer Learning from Deep Features for Remote Sensing and Poverty Mapping [PDF] [Stanford Report] [NYTimes] AAAI-16. In Proc. 30th AAAI Conference on Artificial Intelligence, February 2016.