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Esther Rolf
Esther Rolf
Postdoctoral fellow, Harvard University DSI / CRCS
Dirección de correo verificada de seas.harvard.edu - Página principal
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The effect of large-scale anti-contagion policies on the COVID-19 pandemic
S Hsiang, D Allen, S Annan-Phan, K Bell, I Bolliger, T Chong, ...
Nature 584 (7820), 262-267, 2020
17052020
Delayed impact of fair machine learning
LT Liu, S Dean, E Rolf, M Simchowitz, M Hardt
International Conference on Machine Learning, 3150-3158, 2018
5462018
A generalizable and accessible approach to machine learning with global satellite imagery
E Rolf, J Proctor, T Carleton, I Bolliger, V Shankar, M Ishihara, B Recht, ...
Nature communications 12 (1), 4392, 2021
1042021
Representation matters: Assessing the importance of subgroup allocations in training data
E Rolf, TT Worledge, B Recht, M Jordan
International Conference on Machine Learning, 9040-9051, 2021
352021
A successive-elimination approach to adaptive robotic source seeking
E Rolf, D Fridovich-Keil, M Simchowitz, B Recht, C Tomlin
IEEE Transactions on Robotics, 2020
33*2020
Balancing competing objectives with noisy data: Score-based classifiers for welfare-aware machine learning
E Rolf, M Simchowitz, S Dean, LT Liu, D Bjorkegren, M Hardt, ...
International Conference on Machine Learning, 8158-8168, 2020
302020
Satclip: Global, general-purpose location embeddings with satellite imagery
K Klemmer, E Rolf, C Robinson, L Mackey, M Rußwurm
arXiv preprint arXiv:2311.17179, 2023
222023
Mission Critical--Satellite Data is a Distinct Modality in Machine Learning
E Rolf, K Klemmer, C Robinson, H Kerner
arXiv preprint arXiv:2402.01444, 2024
112024
Geographic location encoding with spherical harmonics and sinusoidal representation networks
M Rußwurm, K Klemmer, E Rolf, R Zbinden, D Tuia
arXiv preprint arXiv:2310.06743, 2023
112023
Post-estimation smoothing: A simple baseline for learning with side information
E Rolf, MI Jordan, B Recht
International Conference on Artificial Intelligence and Statistics, 1759-1769, 2020
102020
Evaluation challenges for geospatial ML
E Rolf
arXiv preprint arXiv:2303.18087, 2023
92023
Resolving label uncertainty with implicit posterior models
E Rolf, N Malkin, A Graikos, A Jojic, C Robinson, N Jojic
arXiv preprint arXiv:2202.14000, 2022
9*2022
Fairness and representation in satellite-based poverty maps: Evidence of urban-rural disparities and their impacts on downstream policy
E Aiken, E Rolf, J Blumenstock
arXiv preprint arXiv:2305.01783, 2023
72023
Reflections from the Workshop on AI-Assisted Decision Making for Conservation
L Xu, E Rolf, S Beery, JR Bennett, T Berger-Wolf, T Birch, E Bondi-Kelly, ...
arXiv preprint arXiv:2307.08774, 2023
42023
Enhancing Wi-Fi Signal Strength of a Dynamic Heterogeneous System Using a Mobile Robot Provider
E Rolf, M Whitlock, BC Min, ET Matson
Robot Intelligence Technology and Applications 2: Results from the 2nd …, 2014
42014
Application-Driven Innovation in Machine Learning
D Rolnick, A Aspuru-Guzik, S Beery, B Dilkina, PL Donti, M Ghassemi, ...
arXiv preprint arXiv:2403.17381, 2024
22024
Ground Control to Major Tom: the importance of field surveys in remotely sensed data analysis
I Bolliger, T Carleton, S Hsiang, J Kadish, J Proctor, B Recht, E Rolf, ...
arXiv preprint arXiv:1710.09342, 2017
22017
Can Strategic Data Collection Improve the Performance of Poverty Prediction Models?
S Soman, E Aiken, E Rolf, J Blumenstock
arXiv preprint arXiv:2211.08735, 2022
12022
Striving for data-model efficiency: Identifying data externalities on group performance
E Rolf, B Packer, A Beutel, F Diaz
arXiv preprint arXiv:2211.06348, 2022
12022
Combining Diverse Information for Coordinated Action: Stochastic Bandit Algorithms for Heterogeneous Agents
L Gordon, E Rolf, M Tambe
arXiv preprint arXiv:2408.03405, 2024
2024
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Artículos 1–20