| Differentially private fine-tuning of language models D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ... International Conference on Learning Representations (ICLR), 2022 | 543 | 2022 |
| Entropy and mutual information in models of deep neural networks M Gabrié, A Manoel, C Luneau, J Barbier, N Macris, F Krzakala, ... Advances in Neural Information Processing Systems (NeurIPS), 1821-1831, 2018 | 260 | 2018 |
| Heterogeneous ensemble knowledge transfer for training large models in federated learning YJ Cho, A Manoel, G Joshi, R Sim, D Dimitriadis Proceedings of the Thirty-First International Joint Conference on Artificial …, 2022 | 205 | 2022 |
| Privacy-preserving in-context learning with differentially private few-shot generation X Tang, R Shin, HA Inan, A Manoel, F Mireshghallah, Z Lin, S Gopi, ... International Conference on Learning Representations (ICLR), 2023 | 109 | 2023 |
| Swept approximate message passing for sparse estimation A Manoel, F Krzakala, E Tramel, L Zdeborova International Conference on Machine Learning (ICML), 1123-1132, 2015 | 91* | 2015 |
| Trojanpuzzle: Covertly poisoning code-suggestion models H Aghakhani, W Dai, A Manoel, X Fernandes, A Kharkar, C Kruegel, ... 2024 IEEE Symposium on Security and Privacy (SP), 1122-1140, 2024 | 84 | 2024 |
| Multi-layer generalized linear estimation A Manoel, F Krzakala, M Mézard, L Zdeborová 2017 IEEE International Symposium on Information Theory (ISIT), 2098-2102, 2017 | 74 | 2017 |
| FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations MDCH Garcia, A Manoel, DD Madrigal, R Sim, D Dimitriadis Workshop on Federated Learning: Recent Advances and New Challenges (in …, 2022 | 73* | 2022 |
| Variational free energies for compressed sensing F Krzakala, A Manoel, EW Tramel, L Zdeborová 2014 IEEE International Symposium on Information Theory (ISIT), 1499-1503, 2014 | 71 | 2014 |
| Federated Survival Analysis with Discrete-Time Cox Models M Andreux, A Manoel, R Menuet, C Saillard, C Simpson International Workshop on Federated Learning for User Privacy and Data …, 2020 | 51 | 2020 |
| Deterministic and generalized framework for unsupervised learning with Restricted Boltzmann Machines EW Tramel, M Gabrié, A Manoel, F Caltagirone, F Krzakala Physical Review X 8 (4), 041006, 2018 | 45 | 2018 |
| Prediction of metabolic syndrome: A machine learning approach to help primary prevention LD Tavares, A Manoel, THR Donato, F Cesena, CA Minanni, ... Diabetes Research and Clinical Practice 191, 110047, 2022 | 40 | 2022 |
| Efficient Per-Example Gradient Computations in Convolutional Neural Networks G Rochette, A Manoel, EW Tramel Workshop on Theory and Practice of Differential Privacy (TPDP), 2020 | 31 | 2020 |
| Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines EW Tramel, A Manoel, F Caltagirone, M Gabrié, F Krzakala 2016 IEEE Information Theory Workshop (ITW), 265-269, 2016 | 25 | 2016 |
| Approximate message-passing for convex optimization with non-separable penalties A Manoel, F Krzakala, G Varoquaux, B Thirion, L Zdeborová arXiv preprint arXiv:1809.06304, 2018 | 24 | 2018 |
| dp-transformers: Training transformer models with differential privacy L Wutschitz, HA Inan, A Manoel | 22 | 2022 |
| Federated Multilingual Models for Medical Transcript Analysis A Manoel, MCH Garcia, T Baumel, S Su, J Chen, R Sim, D Miller, ... Conference on Health, Inference, and Learning, 147-162, 2023 | 15* | 2023 |
| Streaming Bayesian inference: theoretical limits and mini-batch approximate message-passing A Manoel, F Krzakala, EW Tramel, L Zdeborová 2017 55th Annual Allerton Conference on Communication, Control, and …, 2017 | 15 | 2017 |
| Expectation propagation J Raymond, A Manoel, M Opper Statistical Physics, Optimization, Inference, and Message-Passing Algorithms, 2015 | 12 | 2015 |
| Synthetic data privacy metrics A Steier, L Ramaswamy, A Manoel, A Haushalter arXiv preprint arXiv:2501.03941, 2025 | 8 | 2025 |
Robert SimSr. Principal Research Manager, MicrosoftVerified email at microsoft.com
