| 2026 | WACV | Imitating the Functionality of Image-to-Image Models Using a Single Example. | Nurit Spingarn, Tomer Michaeli |
| 2025 | ICCV | Flowedit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models. | Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas, Tomer Michaeli |
| 2025 | ICLR | Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration. | Guy Ohayon, Tomer Michaeli, Michael Elad |
| 2025 | ICML | Compressed Image Generation with Denoising Diffusion Codebook Models. | Guy Ohayon, Hila Manor, Tomer Michaeli, Michael Elad |
| 2025 | ICML | When Diffusion Models Memorize: Inductive Biases in Probability Flow of Minimum-Norm Shallow Neural Nets. | Chen Zeno, Hila Manor, Greg Ongie, Nir Weinberger, Tomer Michaeli, Daniel Soudry |
| 2024 | AAAI | The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank. | Amitay Bar, Rotem Mulayoff, Tomer Michaeli, Ronen Talmon |
| 2024 | COLT | Exact Mean Square Linear Stability Analysis for SGD. | Rotem Mulayoff, Tomer Michaeli |
| 2024 | CVPR | An Edit Friendly DDPM Noise Space: Inversion and Manipulations. | Inbar Huberman-Spiegelglas, Vladimir Kulikov, Tomer Michaeli |
| 2024 | CVPR | Uncertainty Visualization via Low-Dimensional Posterior Projections. | Omer Yair, Elias Nehme, Tomer Michaeli |
| 2024 | ECCV | Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling. | Noam Elata, Tomer Michaeli, Michael Elad |
| 2024 | ICLR | From Posterior Sampling to Meaningful Diversity in Image Restoration. | Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli |
| 2024 | ICLR | On the Posterior Distribution in Denoising: Application to Uncertainty Quantification. | Hila Manor, Tomer Michaeli |
| 2024 | ICML | Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices. | Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas, Tomer Michaeli |
| 2024 | ICML | Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion. | Hila Manor, Tomer Michaeli |
| 2024 | ICML | The Perception-Robustness Tradeoff in Deterministic Image Restoration. | Guy Ohayon, Tomer Michaeli, Michael Elad |
| 2024 | WACV | Nested Diffusion Processes for Anytime Image Generation. | Noam Elata, Bahjat Kawar, Tomer Michaeli, Michael Elad |
| 2024 | SiggraphA | Lumiere: A Space-Time Diffusion Model for Video Generation. | Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Guanghui Liu, Amit Raj, Yuanzhen Li, Michael Rubinstein, Tomer Michaeli, Oliver Wang, Deqing Sun, Tali Dekel, Inbar Mosseri |
| 2023 | CVPR | Internal Diverse Image Completion. | Noa Alkobi, Tamar Rott Shaham, Tomer Michaeli |
| 2023 | CVPR | Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations. | Hagay Michaeli, Tomer Michaeli, Daniel Soudry |
| 2023 | ICLR | The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks. | Mor Shpigel Nacson, Rotem Mulayoff, Greg Ongie, Tomer Michaeli, Daniel Soudry |
| 2023 | ICML | SinDDM: A Single Image Denoising Diffusion Model. | Vladimir Kulikov, Shahar Yadin, Matan Kleiner, Tomer Michaeli |
| 2023 | ICML | Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality. | Guy Ohayon, Theo Joseph Adrai, Michael Elad, Tomer Michaeli |
| 2022 | ECCV | Beyond Local Processing: Adapting CNNs for CT Reconstruction. | Bassel Hamoud, Yuval Bahat, Tomer Michaeli |
| 2022 | ECCV | Power Awareness in Low Precision Neural Networks. | Nurit Spingarn-Eliezer, Ron Banner, Hilla Ben-Yaacov, Elad Hoffer, Tomer Michaeli |
| 2021 | AAAI | Sparsity Aware Normalization for GANs. | Idan Kligvasser, Tomer Michaeli |
| 2021 | CVPR | What's in the Image? Explorable Decoding of Compressed Images. | Yuval Bahat, Tomer Michaeli |
| 2021 | CVPR | Spatially-Adaptive Pixelwise Networks for Fast Image Translation. | Tamar Rott Shaham, Michal Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli |
| 2021 | ICLR | GAN "Steerability" without optimization. | Nurit Spingarn, Ron Banner, Tomer Michaeli |
| 2021 | ICLR | Contrastive Divergence Learning is a Time Reversal Adversarial Game. | Omer Yair, Tomer Michaeli |
| 2020 | CVPR | Explorable Super Resolution. | Yuval Bahat, Tomer Michaeli |
| 2020 | ICML | Unique Properties of Flat Minima in Deep Networks. | Rotem Mulayoff, Tomer Michaeli |
| 2019 | ICCV | SinGAN: Learning a Generative Model From a Single Natural Image. | Tamar Rott Shaham, Tali Dekel, Tomer Michaeli |
| 2019 | ICML | Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff. | Yochai Blau, Tomer Michaeli |
| 2018 | CVPR | The Perception-Distortion Tradeoff. | Yochai Blau, Tomer Michaeli |
| 2018 | CVPR | xUnit: Learning a Spatial Activation Function for Efficient Image Restoration. | Idan Kligvasser, Tamar Rott Shaham, Tomer Michaeli |
| 2018 | CVPR | Deformation Aware Image Compression. | Tamar Rott Shaham, Tomer Michaeli |
| 2018 | CVPR | Deformation Aware Image Compression. | Tamar Rott Shaham, Tomer Michaeli |
| 2018 | CVPR | Modifying Non-Local Variations Across Multiple Views. | Tal Tlusty, Tomer Michaeli, Tali Dekel, Lihi Zelnik-Manor |
| 2018 | CVPR | Multi-Scale Weighted Nuclear Norm Image Restoration. | Noam Yair, Tomer Michaeli |
| 2018 | ECCV | The 2018 PIRM Challenge on Perceptual Image Super-Resolution. | Yochai Blau, Roey Mechrez, Radu Timofte, Tomer Michaeli, Lihi Zelnik-Manor |
| 2018 | ICML | Revealing Common Statistical Behaviors in Heterogeneous Populations. | Andrey Zhitnikov, Rotem Mulayoff, Tomer Michaeli |
| 2016 | ECCV | Visualizing Image Priors. | Tamar Rott Shaham, Tomer Michaeli |
| 2016 | ICML | Nonparametric Canonical Correlation Analysis. | Tomer Michaeli, Weiran Wang, Karen Livescu |
| 2014 | ECCV | Blind Deblurring Using Internal Patch Recurrence. | Tomer Michaeli, Michal Irani |
| 2014 | FUSION | Simultaneous tracking and data association in an extended maneuvering target using the IMM methodology. | Daniel Sigalov, Tomer Michaeli, Yaakov Oshman |
| 2013 | ICCV | Nonparametric Blind Super-resolution. | Tomer Michaeli, Michal Irani |
| 2012 | FUSION | A unified approach to state estimation problems under data and model uncertainties. | Daniel Sigalov, Tomer Michaeli, Yaakov Oshman |
| 2012 | ICASSP | Optimization-based recovery from rate of innovation samples. | Tomer Michaeli, Yonina C. Eldar |
| 2012 | ICASSP | Semi-supervised multi-domain regression with distinct training sets. | Tomer Michaeli, Yonina C. Eldar, Guillermo Sapiro |
| 2011 | ICASSP | Causal signal recovery from U-invariant samples. | Tomer Michaeli, Yonina C. Eldar, Volker Pohl |
| 2010 | ICASSP | Particle filtering based recovery of noisy GARCH processes. | Tomer Michaeli, Israel Cohen |
| 2010 | ICASSP | A minimax approach to Bayesian estimation with partial knowledge of the observation model. | Tomer Michaeli, Yonina C. Eldar |
| 2008 | ICASSP | Constrained nonlinear minimum mse estimation. | Tomer Michaeli, Yonina C. Eldar |
| 2007 | ICASSP | Minimum MSE Estimation with Convex Constraints. | Tomer Michaeli, Yonina C. Eldar |