Search Results for author: Tomer Michaeli

Found 51 papers, 19 papers with code

Unique Properties of Wide Minima in Deep Networks

no code implementations ICML 2020 Rotem Mulayoff, Tomer Michaeli

In this paper, we characterize the wide minima in linear neural networks trained with a quadratic loss.

The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank

no code implementations21 Feb 2024 Amitay Bar, Rotem Mulayoff, Tomer Michaeli, Ronen Talmon

Langevin dynamics (LD) is widely used for sampling from distributions and for optimization.

Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion

no code implementations15 Feb 2024 Hila Manor, Tomer Michaeli

Editing signals using large pre-trained models, in a zero-shot manner, has recently seen rapid advancements in the image domain.

Classification Diffusion Models

no code implementations15 Feb 2024 Shahar Yadin, Noam Elata, Tomer Michaeli

These approaches achieve state-of-the-art results in image, video, and audio generation.

Audio Generation Classification +3

Uncertainty Visualization via Low-Dimensional Posterior Projections

no code implementations12 Dec 2023 Omer Yair, Elias Nehme, Tomer Michaeli

In ill-posed inverse problems, it is commonly desirable to obtain insight into the full spectrum of plausible solutions, rather than extracting only a single reconstruction.

Image Restoration Uncertainty Quantification +1

From Posterior Sampling to Meaningful Diversity in Image Restoration

no code implementations24 Oct 2023 Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli

To accommodate this, many works generate a diverse set of outputs by attempting to randomly sample from the posterior distribution of natural images given the degraded input.

Image Restoration

On the Posterior Distribution in Denoising: Application to Uncertainty Quantification

1 code implementation24 Sep 2023 Hila Manor, Tomer Michaeli

Denoisers play a central role in many applications, from noise suppression in low-grade imaging sensors, to empowering score-based generative models.

Image Denoising Image Restoration +2

The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks

no code implementations30 Jun 2023 Mor Shpigel Nacson, Rotem Mulayoff, Greg Ongie, Tomer Michaeli, Daniel Soudry

Finally, we prove that if a function is sufficiently smooth (in a Sobolev sense) then it can be approximated arbitrarily well using shallow ReLU networks that correspond to stable solutions of gradient descent.

Exact Mean Square Linear Stability Analysis for SGD

no code implementations13 Jun 2023 Rotem Mulayoff, Tomer Michaeli

Furthermore, we show that SGD's stability threshold is equivalent to that of a mixture process which takes in each iteration a full batch gradient step w. p.

Nested Diffusion Processes for Anytime Image Generation

1 code implementation30 May 2023 Noam Elata, Bahjat Kawar, Tomer Michaeli, Michael Elad

Diffusion models are the current state-of-the-art in image generation, synthesizing high-quality images by breaking down the generation process into many fine-grained denoising steps.

Denoising Scheduling +1

GSURE-Based Diffusion Model Training with Corrupted Data

1 code implementation22 May 2023 Bahjat Kawar, Noam Elata, Tomer Michaeli, Michael Elad

Diffusion models have demonstrated impressive results in both data generation and downstream tasks such as inverse problems, text-based editing, classification, and more.

An Edit Friendly DDPM Noise Space: Inversion and Manipulations

2 code implementations12 Apr 2023 Inbar Huberman-Spiegelglas, Vladimir Kulikov, Tomer Michaeli

However, this native noise space does not possess a convenient structure, and is thus challenging to work with in editing tasks.

Denoising

Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models

1 code implementation20 Mar 2023 René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, Tomer Michaeli

Recently, a semantic latent space for DDMs, coined `$h$-space', was shown to facilitate semantic image editing in a way reminiscent of GANs.

Attribute Denoising +1

Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations

1 code implementation CVPR 2023 Hagay Michaeli, Tomer Michaeli, Daniel Soudry

Although CNNs are believed to be invariant to translations, recent works have shown this is not the case, due to aliasing effects that stem from downsampling layers.

Internal Diverse Image Completion

1 code implementation18 Dec 2022 Noa Alkobi, Tamar Rott Shaham, Tomer Michaeli

Image completion is widely used in photo restoration and editing applications, e. g. for object removal.

Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality

no code implementations16 Nov 2022 Guy Ohayon, Theo Adrai, Michael Elad, Tomer Michaeli

Stochastic restoration algorithms allow to explore the space of solutions that correspond to the degraded input.

Energy awareness in low precision neural networks

no code implementations6 Feb 2022 Nurit Spingarn Eliezer, Ron Banner, Elad Hoffer, Hilla Ben-Yaakov, Tomer Michaeli

Power consumption is a major obstacle in the deployment of deep neural networks (DNNs) on end devices.

Quantization

The Implicit Bias of Minima Stability: A View from Function Space

no code implementations NeurIPS 2021 Rotem Mulayoff, Tomer Michaeli, Daniel Soudry

First, we extend the existing knowledge on minima stability to non-differentiable minima, which are common in ReLU nets.

Beyond Quantization: Power aware neural networks

no code implementations29 Sep 2021 Nurit Spingarn, Elad Hoffer, Ron Banner, Hilla Ben Yaacov, Tomer Michaeli

Power consumption is a major obstacle in the deployment of deep neural networks (DNNs) on end devices.

Quantization

A Theory of the Distortion-Perception Tradeoff in Wasserstein Space

no code implementations NeurIPS 2021 Dror Freirich, Tomer Michaeli, Ron Meir

In this paper, we derive a closed form expression for this distortion-perception (DP) function for the mean squared-error (MSE) distortion and the Wasserstein-2 perception index.

Image Restoration Open-Ended Question Answering

Sparsity Aware Normalization for GANs

no code implementations3 Mar 2021 Idan Kligvasser, Tomer Michaeli

Generative adversarial networks (GANs) are known to benefit from regularization or normalization of their critic (discriminator) network during training.

Image-to-Image Translation Translation

GAN "Steerability" without optimization

1 code implementation ICLR 2021 Nurit Spingarn-Eliezer, Ron Banner, Tomer Michaeli

However, all existing techniques rely on an optimization procedure to expose those directions, and offer no control over the degree of allowed interaction between different transformations.

Contrastive Divergence Learning is a Time Reversal Adversarial Game

no code implementations ICLR 2021 Omer Yair, Tomer Michaeli

In this paper, we present an alternative derivation of CD that does not require any approximation and sheds new light on the objective that is actually being optimized by the algorithm.

Learning an optimal PSF-pair for ultra-dense 3D localization microscopy

no code implementations29 Sep 2020 Elias Nehme, Boris Ferdman, Lucien E. Weiss, Tal Naor, Daniel Freedman, Tomer Michaeli, Yoav Shechtman

A long-standing challenge in multiple-particle-tracking is the accurate and precise 3D localization of individual particles at close proximity.

What's in the Image? Explorable Decoding of Compressed Images

no code implementations CVPR 2021 Yuval Bahat, Tomer Michaeli

In spite of this fact, existing decompression algorithms typically produce only a single output, and do not allow the viewer to explore the set of images that map to the given compressed code.

Image Restoration Super-Resolution

Unique Properties of Flat Minima in Deep Networks

no code implementations11 Feb 2020 Rotem Mulayoff, Tomer Michaeli

In this paper, we characterize the flat minima in linear neural networks trained with a quadratic loss.

Explorable Super Resolution

2 code implementations CVPR 2020 Yuval Bahat, Tomer Michaeli

Single image super resolution (SR) has seen major performance leaps in recent years.

Image Super-Resolution

DeepSTORM3D: dense three dimensional localization microscopy and point spread function design by deep learning

1 code implementation21 Jun 2019 Elias Nehme, Daniel Freedman, Racheli Gordon, Boris Ferdman, Lucien E. Weiss, Onit Alalouf, Reut Orange, Tomer Michaeli, Yoav Shechtman

Localization microscopy is an imaging technique in which the positions of individual nanoscale point emitters (e. g. fluorescent molecules) are determined at high precision from their images.

Super-Resolution

The effectiveness of layer-by-layer training using the information bottleneck principle

no code implementations ICLR 2019 Adar Elad, Doron Haviv, Yochai Blau, Tomer Michaeli

The recently proposed information bottleneck (IB) theory of deep nets suggests that during training, each layer attempts to maximize its mutual information (MI) with the target labels (so as to allow good prediction accuracy), while minimizing its MI with the input (leading to effective compression and thus good generalization).

Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff

no code implementations23 Jan 2019 Yochai Blau, Tomer Michaeli

Lossy compression algorithms are typically designed and analyzed through the lens of Shannon's rate-distortion theory, where the goal is to achieve the lowest possible distortion (e. g., low MSE or high SSIM) at any given bit rate.

SSIM

Dense xUnit Networks

1 code implementation27 Nov 2018 Idan Kligvasser, Tomer Michaeli

For example, on ImageNet, our DxNet outperforms a ReLU-based DenseNet having 30% more parameters and achieves state-of-the-art results for this budget of parameters.

Denoising Image Restoration +1

The 2018 PIRM Challenge on Perceptual Image Super-resolution

8 code implementations20 Sep 2018 Yochai Blau, Roey Mechrez, Radu Timofte, Tomer Michaeli, Lihi Zelnik-Manor

This paper reports on the 2018 PIRM challenge on perceptual super-resolution (SR), held in conjunction with the Perceptual Image Restoration and Manipulation (PIRM) workshop at ECCV 2018.

Image Restoration Image Super-Resolution +1

Revealing Common Statistical Behaviors in Heterogeneous Populations

no code implementations ICML 2018 Andrey Zhitnikov, Rotem Mulayoff, Tomer Michaeli

In many areas of neuroscience and biological data analysis, it is desired to reveal common patterns among a group of subjects.

Modifying Non-Local Variations Across Multiple Views

no code implementations CVPR 2018 Tal Tlusty, Tomer Michaeli, Tali Dekel, Lihi Zelnik-Manor

We present an algorithm for modifying small non-local variations between repeating structures and patterns in multiple images of the same scene.

Multi-Scale Weighted Nuclear Norm Image Restoration

no code implementations CVPR 2018 Noam Yair, Tomer Michaeli

A prominent property of natural images is that groups of similar patches within them tend to lie on low-dimensional subspaces.

Deblurring Image Denoising +1

Deformation Aware Image Compression

no code implementations CVPR 2018 Tamar Rott Shaham, Tomer Michaeli

Lossy compression algorithms aim to compactly encode images in a way which enables to restore them with minimal error.

Image Compression SSIM

Deep-STORM: super-resolution single-molecule microscopy by deep learning

3 code implementations29 Jan 2018 Elias Nehme, Lucien E. Weiss, Tomer Michaeli, Yoav Shechtman

We present an ultra-fast, precise, parameter-free method, which we term Deep-STORM, for obtaining super-resolution images from stochastically-blinking emitters, such as fluorescent molecules used for localization microscopy.

Optics

Joint autoencoders: a flexible meta-learning framework

no code implementations ICLR 2018 Baruch Epstein, Ron Meir, Tomer Michaeli

Ideally one would like to allow both the data for the current task and for previous related tasks to self-organize the learning system in such a way that commonalities and differences between the tasks are learned in a data-driven fashion.

Domain Adaptation Meta-Learning +1

xUnit: Learning a Spatial Activation Function for Efficient Image Restoration

1 code implementation CVPR 2018 Idan Kligvasser, Tamar Rott Shaham, Tomer Michaeli

However, state-of-the-art results are typically achieved by very deep networks, which can reach tens of layers with tens of millions of parameters.

Denoising Image Restoration +1

The Perception-Distortion Tradeoff

1 code implementation CVPR 2018 Yochai Blau, Tomer Michaeli

Image restoration algorithms are typically evaluated by some distortion measure (e. g. PSNR, SSIM, IFC, VIF) or by human opinion scores that quantify perceived perceptual quality.

Image Restoration SSIM +1

Joint auto-encoders: a flexible multi-task learning framework

no code implementations30 May 2017 Baruch Epstein. Ron Meir, Tomer Michaeli

Ideally one would like to allow both the data for the current task and for previous related tasks to self-organize the learning system in such a way that commonalities and differences between the tasks are learned in a data-driven fashion.

Domain Adaptation Multi-Task Learning

Non-Redundant Spectral Dimensionality Reduction

no code implementations11 Dec 2016 Yochai Blau, Tomer Michaeli

Our approach relies on replacing the orthogonality constraints underlying those methods by unpredictability constraints.

Dimensionality Reduction

Nonparametric Canonical Correlation Analysis

no code implementations16 Nov 2015 Tomer Michaeli, Weiran Wang, Karen Livescu

Several nonlinear extensions of the original linear CCA have been proposed, including kernel and deep neural network methods.

Representation Learning

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