Minimum MSE Estimation with Convex Constraints. - Tomer Michaeli; Yonina C. Eldar (ICASSP (3), 2007)

Constrained nonlinear minimum mse estimation. - Tomer Michaeli; Yonina C. Eldar (ICASSP, 2008)

Beyond Bandlimited Sampling: Nonlinearities, Smoothness and Sparsity - Yonina C. Eldar; Tomer Michaeli (CoRR, 2008)

Beyond bandlimited sampling. - Yonina C. Eldar; Tomer Michaeli (IEEE Signal Process. Mag., 2009)

High-Rate Interpolation of Random Signals From Nonideal Samples. - Tomer Michaeli; Yonina C. Eldar (IEEE Trans. Signal Process., 2009)

Optimization techniques in modern sampling theory. - Tomer Michaeli; Yonina C. Eldar (Convex Optimization in Signal Processing and Communications, 2010)

Motion blur removal in nonlinear sensors. - Tomer Faktor; Tomer Michaeli; Yonina C. Eldar (Computational Imaging, 2010)

Particle filtering based recovery of noisy GARCH processes. - Tomer Michaeli; Israel Cohen (ICASSP, 2010)

A minimax approach to Bayesian estimation with partial knowledge of the observation model. - Tomer Michaeli; Yonina C. Eldar (ICASSP, 2010)

Nonlinear and Nonideal Sampling Revisited. - Tomer Faktor; Tomer Michaeli; Yonina C. Eldar (IEEE Signal Process. Lett., 2010)

Noninvertible gabor transforms. - Ewa Matusiak; Tomer Michaeli; Yonina C. Eldar (IEEE Trans. Signal Process., 2010)

Linear optimal state estimation in systems with independent mode transitions. - Daniel Sigalov; Tomer Michaeli; Yaakov Oshman (CDC/ECC, 2011)

Causal signal recovery from U-invariant samples. - Tomer Michaeli; Yonina C. Eldar; Volker Pohl (ICASSP, 2011)

Partially Linear Bayesian Estimation with Application to Sparse Approximations - Tomer Michaeli; Daniel Sigalov; Yonina C. Eldar (CoRR, 2011)

Hidden Relationships: Bayesian Estimation With Partial Knowledge. - Tomer Michaeli; Yonina C. Eldar (IEEE Trans. Signal Process., 2011)

U-Invariant Sampling: Extrapolation and Causal Interpolation From Generalized Samples. - Tomer Michaeli; Volker Pohl; Yonina C. Eldar (IEEE Trans. Signal Process., 2011)

A unified approach to state estimation problems under data and model uncertainties. - Daniel Sigalov; Tomer Michaeli; Yaakov Oshman (FUSION, 2012)

Partially Linear Estimation with Application to Image Deblurring Using Blurred/Noisy Image Pairs. - Tomer Michaeli; Daniel Sigalov; Yonina C. Eldar (LVA/ICA, 2012)

Optimization-based recovery from rate of innovation samples. - Tomer Michaeli; Yonina C. Eldar (ICASSP, 2012)

Semi-supervised multi-domain regression with distinct training sets. - Tomer Michaeli; Yonina C. Eldar; Guillermo Sapiro (ICASSP, 2012)

Semi-Supervised Single- and Multi-Domain Regression with Multi-Domain Training - Tomer Michaeli; Yonina C. Eldar; Guillermo Sapiro (CoRR, 2012)

Linear Optimal Estimation in Feedback Hybrid Systems with Application to Tracking in Clutter - Daniel Sigalov; Tomer Michaeli; Yaakov Oshman (CoRR, 2012)

Performance Bounds and Design Criteria for Estimating Finite Rate of Innovation Signals. - Zvika Ben-Haim; Tomer Michaeli; Yonina C. Eldar (IEEE Trans. Inf. Theory, 2012)

Xampling at the Rate of Innovation. - Tomer Michaeli; Yonina C. Eldar (IEEE Trans. Signal Process., 2012)

Partially Linear Estimation With Application to Sparse Signal Recovery From Measurement Pairs. - Tomer Michaeli; Daniel Sigalov; Yonina C. Eldar (IEEE Trans. Signal Process., 2012)

Nonparametric Blind Super-resolution. - Tomer Michaeli; Michal Irani (ICCV, 2013)

Blind Deblurring Using Internal Patch Recurrence. - Tomer Michaeli; Michal Irani (ECCV (3), 2014)

Simultaneous tracking and data association in an extended maneuvering target using the IMM methodology. - Daniel Sigalov; Tomer Michaeli; Yaakov Oshman (FUSION, 2014)

LMMSE Filtering in Feedback Systems With White Random Modes: Application to Tracking in Clutter. - Daniel Sigalov; Tomer Michaeli; Yaakov Oshman (IEEE Trans. Autom. Control., 2014)

Revealing and modifying non-local variations in a single image. - Tali Dekel; Tomer Michaeli; Michal Irani; William T. Freeman (ACM Trans. Graph., 2015)

Visualizing Image Priors. - Tamar Rott Shaham; Tomer Michaeli (ECCV (6), 2016)

Nonparametric Canonical Correlation Analysis. - Tomer Michaeli; Weiran Wang; Karen Livescu (ICML, 2016)

Non-redundant Spectral Dimensionality Reduction. - Yochai Blau; Tomer Michaeli (ECML/PKDD (1), 2017)

Joint auto-encoders: a flexible multi-task learning framework. - Baruch Epstein; Ron Meir; Tomer Michaeli (CoRR, 2017)

The Perception-Distortion Tradeoff. - Yochai Blau; Tomer Michaeli (CVPR, 2018)

xUnit: Learning a Spatial Activation Function for Efficient Image Restoration. - Idan Kligvasser; Tamar Rott Shaham; Tomer Michaeli (CVPR, 2018)

Deformation Aware Image Compression. - Tamar Rott Shaham; Tomer Michaeli (CVPR, 2018)

Modifying Non-Local Variations Across Multiple Views. - Tal Tlusty; Tomer Michaeli; Tali Dekel; Lihi Zelnik-Manor (CVPR, 2018)

Multi-Scale Weighted Nuclear Norm Image Restoration. - Noam Yair; Tomer Michaeli (CVPR, 2018)

The 2018 PIRM Challenge on Perceptual Image Super-Resolution. - Yochai Blau; Roey Mechrez; Radu Timofte; Tomer Michaeli; Lihi Zelnik-Manor (ECCV Workshops (5), 2018)

Revealing Common Statistical Behaviors in Heterogeneous Populations. - Andrey Zhitnikov; Rotem Mulayoff; Tomer Michaeli (ICML, 2018)

Joint Autoencoders: A Flexible Meta-learning Framework. - Baruch Epstein; Ron Meir; Tomer Michaeli (ECML/PKDD (1), 2018)

Dense xUnit Networks. - Idan Kligvasser; Tomer Michaeli (CoRR, 2018)

SinGAN: Learning a Generative Model From a Single Natural Image. - Tamar Rott Shaham; Tali Dekel; Tomer Michaeli (ICCV, 2019)

Direct Validation of the Information Bottleneck Principle for Deep Nets. - Adar Elad; Doron Haviv; Yochai Blau; Tomer Michaeli (ICCV Workshops, 2019)

Multispectral Reconstruction From Reference Objects in the Scene. - Nirit Nussbaum Hoffer; Tomer Michaeli (ICCV Workshops, 2019)

Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff. - Yochai Blau; Tomer Michaeli (ICML, 2019)

On the Minimal Overcompleteness Allowing Universal Sparse Representation. - Rotem Mulayoff; Tomer Michaeli (IEEE Trans. Inf. Theory, 2019)

Explorable Super Resolution. - Yuval Bahat; Tomer Michaeli (CVPR, 2020)

Unique Properties of Flat Minima in Deep Networks. - Rotem Mulayoff; Tomer Michaeli (ICML, 2020)

Unique Properties of Wide Minima in Deep Networks. - Rotem Mulayoff; Tomer Michaeli (CoRR, 2020)

Explorable Decoding of Compressed Images. - Yuval Bahat; Tomer Michaeli (CoRR, 2020)

Learning an optimal PSF-pair for ultra-dense 3D localization microscopy. - Elias Nehme; Boris Ferdman; Lucien E. Weiss; Tal Naor; Daniel Freedman; Tomer Michaeli; Yoav Shechtman (CoRR, 2020)

Sparsity Aware Normalization for GANs. - Idan Kligvasser; Tomer Michaeli (AAAI, 2021)

What's in the Image? Explorable Decoding of Compressed Images. - Yuval Bahat; Tomer Michaeli (CVPR, 2021)

Spatially-Adaptive Pixelwise Networks for Fast Image Translation. - Tamar Rott Shaham; Michaël Gharbi; Richard Zhang 001; Eli Shechtman; Tomer Michaeli (CVPR, 2021)

GAN "Steerability" without optimization. - Nurit Spingarn; Ron Banner; Tomer Michaeli (ICLR, 2021)

Contrastive Divergence Learning is a Time Reversal Adversarial Game. - Omer Yair; Tomer Michaeli (ICLR, 2021)

A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. - Dror Freirich; Tomer Michaeli; Ron Meir (NeurIPS, 2021)

Catch-A-Waveform: Learning to Generate Audio from a Single Short Example. - Gal Greshler; Tamar Rott Shaham; Tomer Michaeli (NeurIPS, 2021)

Deep Self-Dissimilarities as Powerful Visual Fingerprints. - Idan Kligvasser; Tamar Rott Shaham; Yuval Bahat; Tomer Michaeli (NeurIPS, 2021)

The Implicit Bias of Minima Stability: A View from Function Space. - Rotem Mulayoff; Tomer Michaeli; Daniel Soudry (NeurIPS, 2021)

On information rates over a binary input channel. - Michael Peleg; Tomer Michaeli; Shlomo Shamai (CoRR, 2021)

On Information Rates Over a Binary-Input Filtered Gaussian Channel. - Michael Peleg; Tomer Michaeli; Shlomo Shamai (IEEE Open J. Commun. Soc., 2021)

Learning Optimal Wavefront Shaping for Multi-Channel Imaging. - Elias Nehme; Boris Ferdman; Lucien E. Weiss; Tal Naor; Daniel Freedman; Tomer Michaeli; Yoav Shechtman (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Beyond Local Processing: Adapting CNNs for CT Reconstruction. - Bassel Hamoud; Yuval Bahat; Tomer Michaeli (ECCV Workshops (3), 2022)

Power Awareness in Low Precision Neural Networks. - Nurit Spingarn-Eliezer; Ron Banner; Hilla Ben-Yaacov; Elad Hoffer; Tomer Michaeli (ECCV Workshops (7), 2022)

Energy awareness in low precision neural networks. - Nurit Spingarn-Eliezer; Ron Banner; Elad Hoffer; Hilla Ben-Yaacov; Tomer Michaeli (CoRR, 2022)

BlendGAN: Learning and Blending the Internal Distributions of Single Images by Spatial Image-Identity Conditioning. - Idan Kligvasser; Tamar Rott Shaham; Noa Alkobi; Tomer Michaeli (CoRR, 2022)

Internal Diverse Image Completion. - Noa Alkobi; Tamar Rott Shaham; Tomer Michaeli (CVPR Workshops, 2023)

Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations. - Hagay Michaeli; Tomer Michaeli; Daniel Soudry (CVPR, 2023)

The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks. - Mor Shpigel Nacson; Rotem Mulayoff; Greg Ongie; Tomer Michaeli; Daniel Soudry (ICLR, 2023)

SinDDM: A Single Image Denoising Diffusion Model. - Vladimir Kulikov; Shahar Yadin; Matan Kleiner; Tomer Michaeli (ICML, 2023)

Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality. - Guy Ohayon; Theo Joseph Adrai; Michael Elad; Tomer Michaeli (ICML, 2023)

Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration. - Theo Adrai; Guy Ohayon; Michael Elad; Tomer Michaeli (NeurIPS, 2023)

Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint. - Dror Freirich; Tomer Michaeli; Ron Meir (NeurIPS, 2023)

Uncertainty Quantification via Neural Posterior Principal Components. - Elias Nehme; Omer Yair; Tomer Michaeli (NeurIPS, 2023)

Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models. - René Haas; Inbar Huberman-Spiegelglas; Rotem Mulayoff; Tomer Michaeli (CoRR, 2023)

The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank. - Amitay Bar; Rotem Mulayoff; Tomer Michaeli; Ronen Talmon (AAAI, 2024)

Exact Mean Square Linear Stability Analysis for SGD. - Rotem Mulayoff; Tomer Michaeli (COLT, 2024)

An Edit Friendly DDPM Noise Space: Inversion and Manipulations. - Inbar Huberman-Spiegelglas; Vladimir Kulikov; Tomer Michaeli (CVPR, 2024)

Uncertainty Visualization via Low-Dimensional Posterior Projections. - Omer Yair; Elias Nehme; Tomer Michaeli (CVPR, 2024)

Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling. - Noam Elata; Tomer Michaeli; Michael Elad (ECCV (78), 2024)

Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models. - René Haas; Inbar Huberman-Spiegelglas; Rotem Mulayoff; Stella Graßhof; Sami S. Brandt; Tomer Michaeli (FG, 2024)

From Posterior Sampling to Meaningful Diversity in Image Restoration. - Noa Cohen; Hila Manor; Yuval Bahat; Tomer Michaeli (ICLR, 2024)

On the Posterior Distribution in Denoising: Application to Uncertainty Quantification. - Hila Manor; Tomer Michaeli (ICLR, 2024)

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 (ICML, 2024)

Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion. - Hila Manor; Tomer Michaeli (ICML, 2024)

The Perception-Robustness Tradeoff in Deterministic Image Restoration. - Guy Ohayon; Tomer Michaeli; Michael Elad (ICML, 2024)

Hierarchical Uncertainty Exploration via Feedforward Posterior Trees. - Elias Nehme; Rotem Mulayoff; Tomer Michaeli (NeurIPS, 2024)

Perceptual Fairness in Image Restoration. - Guy Ohayon; Michael Elad; Tomer Michaeli (NeurIPS, 2024)

Classification Diffusion Models: Revitalizing Density Ratio Estimation. - Shahar Yadin; Noam Elata; Tomer Michaeli (NeurIPS, 2024)

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; et al. (SIGGRAPH Asia, 2024)

Nested Diffusion Processes for Anytime Image Generation. - Noam Elata; Bahjat Kawar; Tomer Michaeli; Michael Elad (WACV, 2024)

Classification Diffusion Models. - Shahar Yadin; Noam Elata; Tomer Michaeli (CoRR, 2024)

Stealing Image-to-Image Translation Models With a Single Query. - Nurit Spingarn-Eliezer; Tomer Michaeli (CoRR, 2024)

Zero-Shot Image Compression with Diffusion-Based Posterior Sampling. - Noam Elata; Tomer Michaeli; Michael Elad (CoRR, 2024)

Coherence Awareness in Diffractive Neural Networks. - Matan Kleiner; Lior Michaeli; Tomer Michaeli (CoRR, 2024)

FlowEdit: Inversion-Free Text-Based Editing Using Pre-Trained Flow Models. - Vladimir Kulikov; Matan Kleiner; Inbar Huberman-Spiegelglas; Tomer Michaeli (CoRR, 2024)

Generative AI for Solving Inverse Problems in Computational Imaging. - Elias Nehme; Tomer Michaeli (XRDS, 2024)

GSURE-Based Diffusion Model Training with Corrupted Data. - Bahjat Kawar; Noam Elata; Tomer Michaeli; Michael Elad (Trans. Mach. Learn. Res., 2024)

Still-Moving: Customized Video Generation without Customized Video Data. - Hila Chefer; Shiran Zada; Roni Paiss; Ariel Ephrat; Omer Tov; Michael Rubinstein; Lior Wolf; Tali Dekel; Tomer Michaeli; Inbar Mosseri (ACM Trans. Graph., 2024)

Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration. - Guy Ohayon; Tomer Michaeli; Michael Elad (ICLR, 2025)

Convolutional neural networks for predicting the perceived density of large urban fabrics. - Guy Austern; Roei Yosifof; Tomer Michaeli; Shahar Yadin; Dafna Fisher-Gewirtzman (Comput. Environ. Urban Syst., 2025)

Compressed Image Generation with Denoising Diffusion Codebook Models. - Guy Ohayon; Hila Manor; Tomer Michaeli; Michael Elad (CoRR, 2025)

InvFussion: Bridging Supervised and Zero-shot Diffusion for Inverse Problems. - Noam Elata; Hyungjin Chung; Jong Chul Ye; Tomer Michaeli; Michael Elad (CoRR, 2025)

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 (CoRR, 2025)

TokenVerse: Versatile Multi-concept Personalization in Token Modulation Space. - Daniel Garibi; Shahar Yadin; Roni Paiss; Omer Tov; Shiran Zada; Ariel Ephrat; Tomer Michaeli; Inbar Mosseri; Tali Dekel (ACM Trans. Graph., 2025)