Eric W. Tramel, " Generating Zero-Shot Hard-Case Hallucinations: A Synthetic and Open Data Approach ," Databricks Data + AI Summit (San Francisco, USA), 2025.

E. W. Tramel, " Federated Learning: Rewards & Challenges of Distributed Private ML ," Qcon.ai (San Francisco, USA), 2019.

E. W. Tramel, " (Panelist) Federated Learning: ML with Privacy on the Edge ," Fast Forward Labs Webinar, 2018.

E. W. Tramel, " Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines ," International Traveling Workshop on Interactions between Sparse Models and Technology (iTWIST), 2016.

E. W. Tramel, " Introduction to Compressed Sensing ," École de Physique des Houches, «Biophysique: de la Mesure au Modèle en biologie», 2015.

E. W. Tramel, " Discrete Reconstruction for Electron Tomography ," General Congress of the Société Fracaise de Physique, 2015.

E. W. Tramel, " Belief Propagation & Approximations: Discrete Tomography ," Workshop on Sparse Tomographic Reconstruction: Theoretical and Numerical Aspects, 2015.

E. W. Tramel, " A probabilistic approach to compressed sensing: Robust Algorithms ," International Traveling Workshop on Interactions between Sparse Models and Technology (iTWIST), 2014.

Nameyeh Alam & Jake Basilico & Daniele Bertolini & Satish Casie Chetty & Heather D'Angelo & Ryan Douglas & Charles K Fisher & Franklin Fuller & Melissa Gomes & Rishabh Gupta & Alex Lang & Anton Loukianov & Rachel Mak-McCully & Cary Murray & Hanalei Pham & Susanna Qiao & Elena Ryapolova-Webb & Aaron Smith & Dimitri Theoharatos & Anil Tolwani & Eric W Tramel & Anna Vidovszky & Judy Viduya & Jonathan R Walsh, " Digital twin generators for disease modeling ," arXiv preprint arXiv:2405.01488, 2024.

Constance Beguier & Jean Ogier du Terrail & Iqraa Meah & Mathieu Andreux & Eric W Tramel, " Differentially private federated learning for cancer prediction ," arXiv preprint arXiv:2101.02997, 2021.

Constance Beguier & Mathieu Andreux & Eric W Tramel, " Efficient sparse secure aggregation for federated learning ," arXiv preprint, 2020.

G. Rochette, A. Manoel, E. W. Tramel, " Efficient Per-Example Gradient Computations in Convolutional Neural Networks ," arXiv [cs.LG]: 1912.06015, 2019.

P. Courtiol, E. W. Tramel, M. Sanselme, & G. Wainrib, " Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach ," arXiv [stat.ML]: 1802.02212, 2018.

B. Goujaud, E. W. Tramel, P. Courtiol. M. Zaslavskiy, & G. Wainrib, " Robust Detection of Covariate-Treatment Interactions in Clinical Trials ," arXiv [stat.AP]: 1712.08211, 2017.

F.Krzakala, F. Ricci-Tersenghi, L. Zdeborová, R. Zecchina, E. W. Tramel, & L. F. Cugliandolo, " Statistical Physics, Optimization, Inference, and Message-Passing Algorithms ," Oxford University Press, 2016.

James E Fowler and Sungkwang Mun and Eric W Tramel, " Block-based Compressed Sensing of Images and Video ," Foundations and Trends in Signal Processing, 2012.

E. W. Tramel, " Distance-Weighted Regularization for Compressed-Sensing Video Recovery and Supervised Hyperspectral Classification ," Mississippi State University (Dissertation), 2012.

E. W. Tramel, S. Kumar, A. Giurgiu, & A. Montanari, " Statistical Estimation: From Denoising to Sparse Regression and Hidden Cliques ," Statistical Physics, Optimization, Inference, and Message-Passing Algorithms, Oxford University Press, 2016.

Anna A Vidovszky & Charles K Fisher & Anton D Loukianov & Aaron M Smith & Eric W Tramel & Jonathan R Walsh & Jessica L Ross, " Increasing acceptance of AI‐generated digital twins through clinical trial applications ," Clinical and Translational Science, 2024.

C Murray & C Kusiak & A Vanderbeek & D Bertolini & E Tramel, " Boosting Clinical Trial Power in Parkinson's disease (PD) with AI-Generated Digital Twins ," MOVEMENT DISORDERS, 2024.

Jean Ogier du Terrail & Armand Leopold & Clément Joly & Constance Béguier & Mathieu Andreux & Charles Maussion & Benoît Schmauch & Eric W Tramel & Etienne Bendjebbar & Mikhail Zaslavskiy & Gilles Wainrib & Maud Milder & Julie Gervasoni & Julien Guerin & Thierry Durand & Alain Livartowski & Kelvin Moutet & Clément Gautier & Inal Djafar & Anne-Laure Moisson & Camille Marini & Mathieu Galtier & Félix Balazard & Rémy Dubois & Jeverson Moreira & Antoine Simon & Damien Drubay & Magali Lacroix-Triki & Camille Franchet & Guillaume Bataillon & Pierre-Etienne Heudel, " Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer ," Nature Medicine, 2023.

Huili Chen & Jie Ding & Eric Tramel & Shuang Wu & Anit Kumar Sahu & Salman Avestimehr & Tao Zhang, " ActPerFL: Active personalized federated learning ," Amazon Science, 2022.

Mathieu Andreux & Jean Ogier Du Terrail & Constance Beguier & Eric W Tramel, " Siloed federated learning for multi-centric histopathology datasets ," Springer International Publishing, 2020.

M. Zaslavskiy, S. Jégou, E. W. Tramel, & G. Wainrib, " ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors ," Computational Toxicology, 2019.

E. W. Tramel, M. Gabrié, A. Manoel, F. Caltagirone, F. Krzakala, " Deterministic and Generalized Framework for Unsupervised Learning with Restricted Boltzmann Machines ," Physical Review X, 2018.

E. W. Tramel, A. Dremeau, & F. Krzakala, " Approximate Message Passing with Restricted Boltzmann Machine Priors ," Journal of Statistical Mechanics: Theory and Experiment (JSTAT), 2016.

Florent Krzakala & Federico Ricci-Tersenghi & Lenka Zdeborová & Riccardo Zecchina & Eric W Tramel & Leticia F Cugliandolo, " Statistical Physics, Optimization, Inference, and Message-Passing Algorithms: Lecture Notes of the Les Houches School of Physics: Special Issue, October 2013 ," Oxford University Press, 2016.

Boshra Rajaei & Eric W Tramel & Sylvain Gigan & Florent Krzakala & Laurent Daudet, " Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach ," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2016.

M. Trocan, E. W. Tramel, J. E. Fowler, & B. Pesquet-Popescu, " Compressed-Sensing Recovery of Multiview Image and Video Sequences using Signal Prediction ," Multimedia Tools and Applications, 2014.

C. Chen, W. Li, E. W. Tramel, M. Cui, S. Prasad, & J. E. Fowler, " Spectral-Spatial Preprocessing Using Multihypothesis Prediction for Noise-Robust Hyperspectral Image Classification ," IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014.

C. Chen, W. Li, E. W. Tramel, & J. E. Fowler, " Reconstruction of Hyperspectral Imagery from Random Projections using Multihypothesis Prediction ," IEEE Transactions on Geoscience and Remote Sensing, 2014.

W. Li, E. W. Tramel, S. Prasad, & J. E. Fowler, " Nearest Regularized Subspace for Hyperspectral Classification ," IEEE Transactions on Geoscience and Remote Sensing, 2013.

Mathieu Galtier & Mathieu Andreux & Camille Marini & Eric W Tramel & Inal Djafar & Jean du Terrail, " Systems and methods for administrating a federated learning network ," US Patent Application US20240046147A1, 2024.

Pierre Courtiol & Eric W Tramel & Marc Sanselme & Gilles Wainrib, " Systems and methods for image classification ," US Patent US11482022B2, 2022.

Ankit Mohan & Siu-Kei Tin & Eric W Tramel, " Systems and Methods for Compressive Light Sensing Using Multiple Spatial Light Modulators ," US Patent US9160900B2, 2015.

Huili Chen & Jie Ding & Eric W Tramel & Shuang Wu & Anit Kumar Sahu & Salman Avestimehr & Tao Zhang, " Self-aware personalized federated learning ," Advances in Neural Information Processing Systems (NeurIPS), 2022.

Jie Ding & Eric Tramel & Anit Kumar Sahu & Shuang Wu & Salman Avestimehr & Tao Zhang, " Federated learning challenges and opportunities: An outlook ," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022.

A. Manoel, F. Krzakala, E. W. Tramel, & L. Zdeborová, " Streaming Bayesian Inference: Theoretical Limits and Mini-batch Approximate Message-Passing ," Proc. Allerton Conf. on Comm. Control & Comp., 2017.

E. W. Tramel, A. Manoel, F. Caltagirone, M. Gabrié, & F. Krzakala, " Inferring Sparsity: Compressed Sensing using Generalized Restricted Boltzmann Machines ," Proc. IEEE Info. Theory Workshop, 2016.

B. Rajaei, E. W. Tramel, S. Gigan, F. Krzakala, & L. Daudet, " Intensity-only Optical Compressive Imaging Using a Multiply Scattering Material: A Double Phase Retrieval System ," Proc. IEEE Int. Conf. on Acoustics, Speech and Signal Processing (ICASSP), 2016.

J. Barbier, E. W. Tramel, & F. Krzakala, " Scampi: A Robust Approximate Message-Passing Framework for Compressive Imaging ," Proc. Int. Mtg. on High-Dimensional Data Driven Science (HD^3), 2015.

M. Gabrié, E. W. Tramel, & F. Krzakala, " Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy ," Neural Information Processing Systems (NeurIPS), 2015.

A. Manoel, E. W. Tramel, F. Krzakala, & L. Zdeborová, " Sparse Estimation with the Swept Approximated Message-Passing Algorithm ," Proc. Int. Conf. on Machine Learning (ICML), 2015.

F. Krzakala, A. Manoel, E. W. Tramel, & L. Zdeborová, " Variational Free Energies for Compressed Sensing ," Proc. IEEE Int. Symp. on Information Theory (ISIT), 2014.

W. Li, S. Prasad, E. W. Tramel, J. E. Fowler, & Q. Du, " Decision Fusion for Hyperspectral Image Classification Based on Minimum-Distance Classifiers in the Wavelet Domain ," IEEE China Summit on Signal and Info. Processing, 2014.

Chen Chen and Eric W Tramel and James E Fowler, " Compressed-sensing Recovery of Images and Video Using Multihypothesis Predictions ," Asilomar Conference on Signals, Systems, and Computers, 2011.

J. E. Fowler and S. Mun, & E. W. Tramel, " Multiscale Block Compressed Sensing with Smoothed Projected Landweber Reconstruction ," Proc. European Signal Processing Conf. (EUSIPCO), 2011.

E. W. Tramel & J. E. Fowler, " Video Compressed Sensing with Multihypothesis ," Proc. of the IEEE Data Compression Conf. (DCC), 2011.

M. Trocan, T. Maugey, E. W. Tramel, J. E. Fowler, & B. Pesquet-Popescu, " Multistage Compressed-Sensing Reconstruction of Multiview Images ," Proc. of the IEEE Int. Workshop on Multimedia Signal Processing (MMSP), 2010.

M. Trocan, T. Maugey, E. W. Tramel, J. E. Fowler, & B. Pesquet-Popescu, " Compressed Sensing of Multiview Images using Disparity Compensation ," Proc. of the IEEE Int. Conf. on Image Processing (ICIP), 2010.