Compressed sensing of multiview images using disparity compensation. - Maria Trocan; Thomas Maugey; Eric W. Tramel; James E. Fowler; Béatrice Pesquet-Popescu (ICIP, 2010)

Multistage compressed-sensing reconstruction of multiview images. - Maria Trocan; Thomas Maugey; Eric W. Tramel; James E. Fowler; Béatrice Pesquet-Popescu (MMSP, 2010)

Compressed-sensing recovery of images and video using multihypothesis predictions. - Chen Chen 001; Eric W. Tramel; James E. Fowler (ACSCC, 2011)

Video Compressed Sensing with Multihypothesis. - Eric W. Tramel; James E. Fowler (DCC, 2011)

Multiscale block compressed sensing with smoothed projected Landweber reconstruction. - James E. Fowler; Sungkwang Mun; Eric W. Tramel (EUSIPCO, 2011)

Block-Based Compressed Sensing of Images and Video. - James E. Fowler; Sungkwang Mun; Eric W. Tramel (Found. Trends Signal Process., 2012)

Decision fusion for hyperspectral image classification based on minimum-distance classifiers in thewavelet domain. - Wei Li 032; Saurabh Prasad; Eric W. Tramel; James E. Fowler; Qian Du 001 (ChinaSIP, 2014)

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)

Statistical Estimation: From Denoising to Sparse Regression and Hidden Cliques. - Eric W. Tramel; Santhosh Kumar; Andrei Giurgiu; Andrea Montanari (CoRR, 2014)

Compressed-sensing recovery of multiview image and video sequences using signal prediction. - Maria Trocan; Eric W. Tramel; James E. Fowler; Béatrice Pesquet (Multim. Tools Appl., 2014)

Spectral-Spatial Preprocessing Using Multihypothesis Prediction for Noise-Robust Hyperspectral Image Classification. - Chen Chen 001; Wei Li 032; Eric W. Tramel; Minshan Cui; Saurabh Prasad; James E. Fowler (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014)

Reconstruction of Hyperspectral Imagery From Random Projections Using Multihypothesis Prediction. - Chen Chen 001; Wei Li 032; Eric W. Tramel; James E. Fowler (IEEE Trans. Geosci. Remote. Sens., 2014)

Nearest Regularized Subspace for Hyperspectral Classification. - Wei Li 032; Eric W. Tramel; Saurabh Prasad; James E. Fowler (IEEE Trans. Geosci. Remote. Sens., 2014)

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

Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy. - Marylou Gabrié; Eric W. Tramel; Florent Krzakala (NIPS, 2015)

Scampi: a robust approximate message-passing framework for compressive imaging. - Jean Barbier; Eric W. Tramel; Florent Krzakala (CoRR, 2015)

Training Restricted Boltzmann Machines via the Thouless-Anderson-Palmer Free Energy. - Marylou Gabrié; Eric W. Tramel; Florent Krzakala (CoRR, 2015)

Intensity-only optical compressive imaging using a multiply scattering material : a double phase retrieval system. - Boshra Rajaei; Eric W. Tramel; Sylvain Gigan; Florent Krzakala; Laurent Daudet (CoRR, 2015)

Approximate Message Passing with Restricted Boltzmann Machine Priors. - Eric W. Tramel; Angélique Drémeau; Florent Krzakala (CoRR, 2015)

Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach. - Boshra Rajaei; Eric W. Tramel; Sylvain Gigan; Florent Krzakala; Laurent Daudet (ICASSP, 2016)

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)

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)

Classification and Disease Localization in Histopathology Using Only Global Labels: A Weakly-Supervised Approach. - Pierre Courtiol; Eric W. Tramel; Marc Sanselme; Gilles Wainrib (CoRR, 2018)

ToxicBlend: Virtual Screening of Toxic Compounds with Ensemble Predictors. - Mikhail Zaslavskiy; Simon Jégou; Eric W. Tramel; Gilles Wainrib (CoRR, 2018)

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

Siloed Federated Learning for Multi-centric Histopathology Datasets. - Mathieu Andreux; Jean Ogier du Terrail; Constance Beguier; Eric W. Tramel (DART/DCL@MICCAI, 2020)

SAFER: Sparse secure Aggregation for FEderated leaRning. - Constance Beguier; Eric W. Tramel (CoRR, 2020)

Differentially Private Federated Learning for Cancer Prediction. - Constance Beguier; Jean Ogier du Terrail; Iqraa Meah; Mathieu Andreux; Eric W. Tramel (CoRR, 2021)

Federated Learning Challenges and Opportunities: An Outlook. - Jie Ding 002; Eric W. Tramel; Anit Kumar Sahu; Shuang Wu; Salman Avestimehr; Tao Zhang (ICASSP, 2022)

Self-Aware Personalized Federated Learning. - Huili Chen; Jie Ding 002; Eric W. Tramel; Shuang Wu; Anit Kumar Sahu; Salman Avestimehr; Tao Zhang (NeurIPS, 2022)

Semi-Supervised Federated Learning for Keyword Spotting. - Enmao Diao; Eric W. Tramel; Jie Ding 002; Tao Zhang (ICME Workshops, 2023)

Digital Twin Generators for Disease Modeling. - Nameyeh Alam; Jake Basilico; Daniele Bertolini; Satish Casie Chetty; Heather D'Angelo; Ryan Douglas; Charles K. Fisher; Franklin Fuller; Melissa Gomes; Rishabh Gupta; Alex H. Lang; Anton Loukianov; et al. (CoRR, 2024)