Statistical mechanics of reputation systems in autonomous networks - Andre Manoel; Renato Vicente (CoRR, 2012)

Variational free energies for compressed sensing. - Florent Krzakala; Andre Manoel; Eric W. Tramel; Lenka Zdeborová (ISIT, 2014)

Sparse Estimation with the Swept Approximated Message-Passing Algorithm. - Andre Manoel; Florent Krzakala; Eric W. Tramel; Lenka Zdeborová (CoRR, 2014)

Swept Approximate Message Passing for Sparse Estimation. - Andre Manoel; Florent Krzakala; Eric W. Tramel; Lenka Zdeborová (ICML, 2015)

Inferring sparsity: Compressed sensing using generalized restricted Boltzmann machines. - Eric W. Tramel; Andre Manoel; Francesco Caltagirone; Marylou Gabrié; Florent Krzakala (ITW, 2016)

Proceedings of the third "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'16). - Vinayak Abrol; Olivier Absil; Pierre-Antoine Absil; Sandrine Anthoine; Philippe Antoine; Thomas Arildsen; Nancy Bertin; Folkert Bleichrodt; Jérôme Bobin; Anne Bol; Antoine Bonnefoy; Francesco Caltagirone; et al. (CoRR, 2016)

Streaming Bayesian inference: Theoretical limits and mini-batch approximate message-passing. - Andre Manoel; Florent Krzakala; Eric W. Tramel; Lenka Zdeborová (Allerton, 2017)

Multi-layer generalized linear estimation. - Andre Manoel; Florent Krzakala; Marc Mézard; Lenka Zdeborová (ISIT, 2017)

A Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines. - Eric W. Tramel; Marylou Gabrié; Andre Manoel; Francesco Caltagirone; Florent Krzakala (CoRR, 2017)

Entropy and mutual information in models of deep neural networks. - Marylou Gabrié; Andre Manoel; Clément Luneau; Jean Barbier; Nicolas Macris; Florent Krzakala; Lenka Zdeborová (NeurIPS, 2018)

Approximate message-passing for convex optimization with non-separable penalties. - Andre Manoel; Florent Krzakala; Gaël Varoquaux; Bertrand Thirion; Lenka Zdeborová (CoRR, 2018)

Efficient Per-Example Gradient Computations in Convolutional Neural Networks. - Gaspar Rochette; Andre Manoel; Eric W. Tramel (CoRR, 2019)

Federated Survival Analysis with Discrete-Time Cox Models. - Mathieu Andreux; Andre Manoel; Romuald Menuet; Charlie Saillard; Chloé Simpson (CoRR, 2020)

Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning. - Yae Jee Cho; Andre Manoel; Gauri Joshi; Robert Sim; Dimitrios Dimitriadis (IJCAI, 2022)

FLUTE: A Scalable, Extensible Framework for High-Performance Federated Learning Simulations. - Dimitrios Dimitriadis; Mirian Hipolito Garcia; Daniel Madrigal Diaz; Andre Manoel; Robert Sim (CoRR, 2022)

Federated Multilingual Models for Medical Transcript Analysis. - Andre Manoel; Mirian del Carmen Hipolito Garcia; Tal Baumel; Shize Su; Jialei Chen 003; Robert Sim; Dan Miller; Danny Karmon; Dimitrios Dimitriadis (CHIL, 2023)

Federated Learning Toolkit with Voice-based User Verification Demo. - Prathamesh Mandke; Rachel Oberst; Matthias Reisser; Avijit Chakraborty; Christos Louizos; Joseph Soriaga; Daniel Madrigal Diaz; Andre Manoel; Nalin Singal; Jeff Omhover; Robert Sim (INTERSPEECH, 2023)

Project Florida: Federated Learning Made Easy. - Daniel Madrigal Diaz; Andre Manoel; Jialei Chen 003; Nalin Singal; Robert Sim (CoRR, 2023)

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation. - Xinyu Tang 003; Richard Shin; Huseyin A. Inan; Andre Manoel; Fatemehsadat Mireshghallah; Zinan Lin 001; Sivakanth Gopi; Janardhan Kulkarni; Robert Sim (ICLR, 2024)

TrojanPuzzle: Covertly Poisoning Code-Suggestion Models. - Hojjat Aghakhani; Wei Dai 007; Andre Manoel; Xavier Fernandes; Anant Kharkar; Christopher Kruegel; Giovanni Vigna; David Evans 001; Ben Zorn 001; Robert Sim (SP, 2024)

Controllable Synthetic Clinical Note Generation with Privacy Guarantees. - Tal Baumel; Andre Manoel; Daniel Jones; Shize Su; Huseyin A. Inan; Aaron Bornstein; Robert Sim (CoRR, 2024)

Differentially Private Fine-tuning of Language Models. - Da Yu; Saurabh Naik; Arturs Backurs; Sivakanth Gopi; Huseyin A. Inan; Gautam Kamath 001; Janardhan Kulkarni; Yin Tat Lee; Andre Manoel; Lukas Wutschitz; Sergey Yekhanin; Huishuai Zhang (J. Priv. Confidentiality, 2024)

Synthetic Data Privacy Metrics. - Amy Steier; Lipika Ramaswamy; Andre Manoel; Alexa Haushalter (CoRR, 2025)