Improved frame-to-frame pose tracking during vision-only SLAM/SFM with a tumbling target. - Sean Augenstein; Stephen M. Rock (ICRA, 2011)

Tumbling target reconstruction and pose estimation through fusion of monocular vision and sparse-pattern range data. - Jose Padial; Marcus Hammond; Sean Augenstein; Stephen M. Rock (MFI, 2012)

Optimal Scheduling of Earth-Imaging Satellites with Human Collaboration via Directed Acyclic Graphs. - Sean Augenstein (AAAI Spring Symposia, 2014)

Optimal Scheduling of a Constellation of Earth-Imaging Satellites, for Maximal Data Throughput and Efficient Human Management. - Sean Augenstein; Alejandra Estanislao; Emmanuel Guere; Sean Blaes (ICAPS, 2016)

Federated Learning for Mobile Keyboard Prediction. - Andrew Hard; Kanishka Rao; Rajiv Mathews; Françoise Beaufays; Sean Augenstein; Hubert Eichner; Chloé Kiddon; Daniel Ramage (CoRR, 2018)

Generative Models for Effective ML on Private, Decentralized Datasets. - Sean Augenstein; H. Brendan McMahan; Daniel Ramage; Swaroop Ramaswamy; Peter Kairouz; Mingqing Chen; Rajiv Mathews; Blaise Agüera y Arcas (ICLR, 2020)

Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift. - Sean Augenstein; Andrew Hard; Kurt Partridge; Rajiv Mathews (CoRR, 2021)

Production federated keyword spotting via distillation, filtering, and joint federated-centralized training. - Andrew Hard; Kurt Partridge; Neng Chen; Sean Augenstein; Aishanee Shah; Hyun Jin Park; Alex Park 001; Sara Ng; Jessica Nguyen; Ignacio López-Moreno; Rajiv Mathews; Françoise Beaufays (INTERSPEECH, 2022)

Mixed Federated Learning: Joint Decentralized and Centralized Learning. - Sean Augenstein; Andrew Hard; Lin Ning 001; Karan Singhal; Satyen Kale; Kurt Partridge; Rajiv Mathews (CoRR, 2022)

Learning to Generate Image Embeddings with User-Level Differential Privacy. - Zheng Xu 002; Maxwell D. Collins; Yuxiao Wang 001; Liviu Panait; Sewoong Oh; Sean Augenstein; Ting Liu 005; Florian Schroff; H. Brendan McMahan (CVPR, 2023)

Learning from straggler clients in federated learning. - Andrew Hard; Antonious M. Girgis; Ehsan Amid; Sean Augenstein; Lara McConnaughey; Rajiv Mathews; Rohan Anil (CoRR, 2024)

Cascade-Aware Training of Language Models. - Congchao Wang; Sean Augenstein; Keith Rush; Wittawat Jitkrittum; Harikrishna Narasimhan; Ankit Singh Rawat; Aditya Krishna Menon; Alec Go (CoRR, 2024)

I Know What I Don't Know: Improving Model Cascades Through Confidence Tuning. - Stephan Rabanser; Nathalie Rauschmayr; Achin Kulshrestha; Petra Poklukar; Wittawat Jitkrittum; Sean Augenstein; Congchao Wang; Federico Tombari (CoRR, 2025)