Population Expansion for Training Language Models with Private Federated Learning. - Tatsuki Koga; Congzheng Song; Martin Pelikan; Mona Chitnis (CoRR, 2023)

Samplable Anonymous Aggregation for Private Federated Data Analysis. - Kunal Talwar; Shan Wang; Audra McMillan; Vojta Jina; Vitaly Feldman; Bailey Basile; Áine Cahill; Yi Sheng Chan; Mike Chatzidakis; Junye Chen; Oliver R. A. Chick; Mona Chitnis; et al. (CoRR, 2023)

Levelized cost estimates of solar photovoltaic electricity in the United Kingdom until 2035. - Filip Mandys; Mona Chitnis; S. Ravi P. Silva (Patterns, 2023)

Response to "Low cost, uncertain value: Why cheap PV may still not become UK's main power source". - Filip Mandys; Mona Chitnis; S. Ravi P. Silva (Patterns, 2023)

Samplable Anonymous Aggregation for Private Federated Data Analysis. - Kunal Talwar; Shan Wang; Audra McMillan; Vitaly Feldman; Pansy Bansal; Bailey Basile; Áine Cahill; Yi Sheng Chan; Mike Chatzidakis; Junye Chen; Oliver R. A. Chick; Mona Chitnis; et al. (CCS, 2024)

pfl-research: simulation framework for accelerating research in Private Federated Learning. - Filip Granqvist; Congzheng Song; Áine Cahill; Rogier C. van Dalen; Martin Pelikan; Yi Sheng Chan; Xiaojun Feng; Natarajan Krishnaswami; Vojta Jina; Mona Chitnis (NeurIPS, 2024)

Momentum Approximation in Asynchronous Private Federated Learning. - Tao Yu; Congzheng Song; Jianyu Wang; Mona Chitnis (CoRR, 2024)

Private Federated Learning In Real World Application - A Case Study. - An Ji; Bortik Bandyopadhyay; Congzheng Song; Natarajan Krishnaswami; Prabal Vashisht; Rigel Smiroldo; Isabel Litton; Sayantan Mahinder; Mona Chitnis; Andrew W. Hill (CoRR, 2025)