| Federated learning for mobile keyboard prediction A Hard, K Rao, R Mathews, S Ramaswamy, F Beaufays, S Augenstein, ... arXiv preprint arXiv:1811.03604, 2018 | 1707 | 2018 |
| Generative models for effective ML on private, decentralized datasets S Augenstein, HB McMahan, D Ramage, S Ramaswamy, P Kairouz, ... arXiv preprint arXiv:1911.06679, 2019 | 211 | 2019 |
| Origins of large crescent-shaped bedforms within the axial channel of Monterey Canyon, offshore California CK Paull, W Ussler III, DW Caress, E Lundsten, JA Covault, KL Maier, ... Geology 6 (6), 755-774, 2010 | 172 | 2010 |
| Federated learning for mobile keyboard prediction (2018) A Hard, K Rao, R Mathews, S Ramaswamy, F Beaufays, S Augenstein, ... arXiv preprint arXiv:1811.03604, 1811 | 66 | 1811 |
| Improved frame-to-frame pose tracking during vision-only SLAM/SFM with a tumbling target S Augenstein, SM Rock 2011 IEEE International Conference on Robotics and Automation, 3131-3138, 2011 | 64 | 2011 |
| Optimal scheduling of a constellation of earth-imaging satellites, for maximal data throughput and efficient human management S Augenstein, A Estanislao, E Guere, S Blaes Proceedings of the International Conference on Automated Planning and …, 2016 | 61 | 2016 |
| Satellite scheduling system S Augenstein, JM Mann, D Berkenstock US Patent 9,262,734, 2016 | 55 | 2016 |
| Satellite scheduling system using crowd-sourced data JM Mann, D Berkenstock, S Augenstein US Patent 8,977,619, 2015 | 45 | 2015 |
| Federated learning for mobile keyboard prediction. arXiv 2018 A Hard, K Rao, R Mathews, S Ramaswamy, F Beaufays, S Augenstein, ... arXiv preprint arXiv:1811.03604, 2018 | 44 | 2018 |
| Monocular pose and shape estimation of moving targets, for autonomous rendezvous and docking S Augenstein Stanford University, 2011 | 29 | 2011 |
| Simultaneous Estimation of Target Pose and 3-D Shape Using the FastSLAM Algorithm S Augenstein, S Rock AIAA Guidance, Navigation, and Control Conference, 5782, 2009 | 27 | 2009 |
| Optimal scheduling of earth-imaging satellites with human collaboration via directed acyclic graphs S Augenstein 2014 AAAI Spring Symposium Series, 2014 | 22 | 2014 |
| Learning to generate image embeddings with user-level differential privacy Z Xu, M Collins, Y Wang, L Panait, S Oh, S Augenstein, T Liu, F Schroff, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 21 | 2023 |
| Satellite scheduling system S Augenstein, JM Mann, D Berkenstock US Patent 9,996,810, 2018 | 18 | 2018 |
| Tumbling target reconstruction and pose estimation through fusion of monocular vision and sparse-pattern range data J Padial, M Hammond, S Augenstein, SM Rock 2012 IEEE International Conference on Multisensor Fusion and Integration for …, 2012 | 16 | 2012 |
| Production federated keyword spotting via distillation, filtering, and joint federated-centralized training A Hard, K Partridge, N Chen, S Augenstein, A Shah, HJ Park, A Park, ... arXiv preprint arXiv:2204.06322, 2022 | 14 | 2022 |
| Estimating inertial position and current in the midwater S Augenstein, S Rock OCEANS 2008, 1-6, 2008 | 14 | 2008 |
| & Ramage, D.(2018). Federated learning for mobile keyboard prediction A Hard, K Rao, R Mathews, S Ramaswamy, F Beaufays, S Augenstein, ... arXiv preprint arXiv:1811.03604, 2018 | 12 | 2018 |
| Mixed federated learning: Joint decentralized and centralized learning S Augenstein, A Hard, L Ning, K Singhal, S Kale, K Partridge, R Mathews arXiv preprint arXiv:2205.13655, 2022 | 8 | 2022 |
| Jointly learning from decentralized (federated) and centralized data to mitigate distribution shift S Augenstein, A Hard, K Partridge, R Mathews arXiv preprint arXiv:2111.12150, 2021 | 6 | 2021 |
