Esther Rolf

According to our database, Esther Rolf authored at least 27 papers between 2013 and 2025.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2025

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery.

Arjun Rao, Esther Rolf

CoRR, July, 2025

How Does the Spatial Distribution of Pre-training Data Affect Geospatial Foundation Models?

Mirali Purohit, Gedeon Muhawenayo, Esther Rolf, Hannah Kerner

CoRR, January, 2025

Classification Drives Geographic Bias in Street Scene Segmentation.

Rahul Nair, Bhanu Tokas, Gabriel Tseng, Esther Rolf, Hannah Kerner

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2025

SatCLIP: Global, General-Purpose Location Embeddings with Satellite Imagery.

Konstantin Klemmer, Esther Rolf, Caleb Robinson, Lester Mackey, Marc Rußwurm

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas.

Esther Rolf, Lucia Gordon, Milind Tambe, Andrew Davies

CoRR, 2024

Application-Driven Innovation in Machine Learning.

David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White

CoRR, 2024

Mission Critical - Satellite Data is a Distinct Modality in Machine Learning.

Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner

CoRR, 2024

Position: Application-Driven Innovation in Machine Learning.

David Rolnick, Alán Aspuru-Guzik, Sara Beery, Bistra Dilkina, Priya L. Donti, Marzyeh Ghassemi, Hannah Kerner, Claire Monteleoni, Esther Rolf, Milind Tambe, Adam White

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Mission Critical - Satellite Data is a Distinct Modality in Machine Learning.

Esther Rolf, Konstantin Klemmer, Caleb Robinson, Hannah Kerner

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Geographic Location Encoding with Spherical Harmonics and Sinusoidal Representation Networks.

Marc Rußwurm, Konstantin Klemmer, Esther Rolf, Robin Zbinden, Devis Tuia

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents.

Lucia Gordon, Esther Rolf, Milind Tambe

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023

Reflections from the Workshop on AI-Assisted Decision Making for Conservation.

Lily Xu, Esther Rolf, Sara Beery, Joseph R. Bennett, Tanya Y. Berger-Wolf, Tanya Birch, Elizabeth Bondi-Kelly, Justin Brashares, Melissa S. Chapman, Anthony Corso, Andrew Davies, Nikhil Garg, Angela Gaylard, Robert Heilmayr, Hannah Kerner, Konstantin Klemmer, Vipin Kumar, Lester Mackey, Claire Monteleoni, Paul Moorcroft, Jonathan Palmer, Andrew Perrault, David Thau, Milind Tambe

CoRR, 2023

Evaluation Challenges for Geospatial ML.

Esther Rolf

CoRR, 2023

Fairness and Representation in Satellite-Based Poverty Maps: Evidence of Urban-Rural Disparities and Their Impacts on Downstream Policy.

Emily L. Aiken, Esther Rolf, Joshua Blumenstock

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

2022

Incorporating Intent, Impact, and Context for Beneficial Machine Learning

Esther Rolf

PhD thesis, 2022

Can Strategic Data Collection Improve the Performance of Poverty Prediction Models?

Satej Soman, Emily L. Aiken, Esther Rolf, Joshua Blumenstock

CoRR, 2022

Striving for data-model efficiency: Identifying data externalities on group performance.

Esther Rolf, Ben Packer, Alex Beutel, Fernando Diaz

CoRR, 2022

Resolving label uncertainty with implicit posterior models.

Esther Rolf, Nikolay Malkin, Alexandros Graikos, Ana Jojic, Caleb Robinson, Nebojsa Jojic

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2021

A Successive-Elimination Approach to Adaptive Robotic Source Seeking.

Esther Rolf, David Fridovich-Keil, Max Simchowitz, Benjamin Recht, Claire J. Tomlin

IEEE Trans. Robotics, 2021

Representation Matters: Assessing the Importance of Subgroup Allocations in Training Data.

Esther Rolf, Theodora T. Worledge, Benjamin Recht, Michael I. Jordan

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery.

Esther Rolf, Jonathan Proctor, Tamma Carleton, Ian Bolliger, Vaishaal Shankar, Miyabi Ishihara, Benjamin Recht, Solomon Hsiang

CoRR, 2020

Balancing Competing Objectives with Noisy Data: Score-Based Classifiers for Welfare-Aware Machine Learning.

Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu, Daniel Björkegren, Moritz Hardt, Joshua Blumenstock

Proceedings of the 37th International Conference on Machine Learning, 2020

Post-Estimation Smoothing: A Simple Baseline for Learning with Side Information.

Esther Rolf, Michael I. Jordan, Benjamin Recht

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2018

A Successive-Elimination Approach to Adaptive Robotic Sensing.

Esther Rolf, David Fridovich-Keil, Max Simchowitz, Benjamin Recht, Claire J. Tomlin

CoRR, 2018

Delayed Impact of Fair Machine Learning.

Lydia T. Liu, Sarah Dean, Esther Rolf, Max Simchowitz, Moritz Hardt

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis.

Ian Bolliger, Tamma Carleton, Solomon Hsiang, Jonathan Kadish, Jonathan Proctor, Benjamin Recht, Esther Rolf, Vaishaal Shankar

CoRR, 2017

2013

Enhancing Wi-Fi Signal Strength of a Dynamic Heterogeneous System Using a Mobile Robot Provider.

Esther Rolf, Matt Whitlock, Byung-Cheol Min, Eric T. Matson

Proceedings of the Robot Intelligence Technology and Applications 2, 2013