Meirav Galun | DeepAI

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∙ 07/26/2023

Controlling the Inductive Bias of Wide Neural Networks by Modifying the Kernel's Spectrum

Wide neural networks are biased towards learning certain functions, infl...

0 Amnon Geifman, et al. ∙

∙ 11/27/2022

GRelPose: Generalizable End-to-End Relative Camera Pose Regression

This paper proposes a generalizable, end-to-end deep learning-based meth...

0 Fadi Khatib, et al. ∙

∙ 11/27/2022

A Kernel Perspective of Skip Connections in Convolutional Networks

Over-parameterized residual networks (ResNets) are amongst the most succ...

0 Daniel Barzilai, et al. ∙

∙ 03/17/2022

On the Spectral Bias of Convolutional Neural Tangent and Gaussian Process Kernels

We study the properties of various over-parametrized convolutional neura...

13 Amnon Geifman, et al. ∙

∙ 04/14/2021

Deep Permutation Equivariant Structure from Motion

Existing deep methods produce highly accurate 3D reconstructions in ster...

0 Dror Moran, et al. ∙

∙ 04/07/2021

Spectral Analysis of the Neural Tangent Kernel for Deep Residual Networks

Deep residual network architectures have been shown to achieve superior ...

0 Yuval Belfer, et al. ∙

∙ 10/28/2020

Point of Care Image Analysis for COVID-19

Early detection of COVID-19 is key in containing the pandemic. Disease d...

0 Daniel Yaron, et al. ∙

∙ 07/03/2020

On the Similarity between the Laplace and Neural Tangent Kernels

Recent theoretical work has shown that massively overparameterized neura...

0 Amnon Geifman, et al. ∙

∙ 03/12/2020

Learning Algebraic Multigrid Using Graph Neural Networks

Efficient numerical solvers for sparse linear systems are crucial in sci...

0 Ilay Luz, et al. ∙

∙ 03/10/2020

Frequency Bias in Neural Networks for Input of Non-Uniform Density

Recent works have partly attributed the generalization ability of over-p...

10 Ronen Basri, et al. ∙

∙ 11/30/2019

Averaging Essential and Fundamental Matrices in Collinear Camera Settings

Global methods to Structure from Motion have gained popularity in recent...

0 Amnon Geifman, et al. ∙

∙ 04/04/2019

Algebraic Characterization of Essential Matrices and Their Averaging in Multiview Settings

Essential matrix averaging, i.e., the task of recovering camera location...

0 Yoni Kasten, et al. ∙

∙ 02/25/2019

Learning to Optimize Multigrid PDE Solvers

Constructing fast numerical solvers for partial differential equations (...

0 Daniel Greenfeld, et al. ∙

∙ 01/27/2019

Resultant Based Incremental Recovery of Camera Pose from Pairwise Matches

Incremental (online) structure from motion pipelines seek to recover the...

0 Yoni Kasten, et al. ∙

∙ 12/02/2018

GPSfM: Global Projective SFM Using Algebraic Constraints on Multi-View Fundamental Matrices

This paper addresses the problem of recovering projective camera matrice...

0 Yoni Kasten, et al. ∙

∙ 06/22/2017

On Detection of Faint Edges in Noisy Images

A fundamental question for edge detection in noisy images is how faint c...

0 Nati Ofir, et al. ∙

∙ 02/10/2017

A New Rank Constraint on Multi-view Fundamental Matrices, and its Application to Camera Location Recovery

Accurate estimation of camera matrices is an important step in structure...

0 Soumyadip Sengupta, et al. ∙

∙ 06/10/2015

Wide baseline stereo matching with convex bounded-distortion constraints

Finding correspondences in wide baseline setups is a challenging problem...

0 Meirav Galun, et al. ∙

∙ 10/26/2012

A Multiscale Framework for Challenging Discrete Optimization

Current state-of-the-art discrete optimization methods struggle behind w...

0 Shai Bagon, et al. ∙

∙ 04/22/2012

A Unified Multiscale Framework for Discrete Energy Minimization

Discrete energy minimization is a ubiquitous task in computer vision, ye...

0 Shai Bagon, et al. ∙

∙ 12/13/2011

Large Scale Correlation Clustering Optimization

Clustering is a fundamental task in unsupervised learning. The focus of ...

0 Shai Bagon, et al. ∙

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