Michael M. Bronstein

发表

Analysis of Two-Dimensional Non-Rigid Shapes

Alfred M. Bruckstein, Alexander M. Bronstein, Ron Kimmel, 2008, International Journal of Computer Vision.

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2009, IPSJ Trans. Comput. Vis. Appl..

LDAHash: Improved Matching with Smaller Descriptors

Pascal Fua, Alexander M. Bronstein, Christoph Strecha, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Volumetric heat kernel signatures

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2010, 3DOR '10.

Putting the Pieces Together: Regularized Multi-part Shape Matching

Alexander M. Bronstein, Michael M. Bronstein, Or Litany, 2012, ECCV Workshops.

Latent-Graph Learning for Disease Prediction

Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein, 2020, International Conference on Medical Image Computing and Computer-Assisted Intervention.

Motion-based mesh segmentation using augmented silhouettes

Roberto Scopigno, Michael M. Bronstein, Kai Hormann, 2012, Graph. Model..

Affine-Invariant Photometric Heat Kernel Signatures

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2012, 3DOR@Eurographics.

Matching Two-Dimensional Articulated Shapes Using Generalized Multidimensional Scaling

Alfred M. Bruckstein, Alexander M. Bronstein, Ron Kimmel, 2006, AMDO.

A Correspondence-Less Approach to Matching of Deformable Shapes

Alexander M. Bronstein, Michael M. Bronstein, Jonathan Pokrass, 2011, SSVM.

Blind Source Separation Using the Block-Coordinate Relative Newton Method

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2004, ICA.

Shape Palindromes: Analysis of Intrinsic Symmetries in 2D Articulated Shapes

Radu Horaud, Alexander M. Bronstein, Michael M. Bronstein, 2011, SSVM.

Stable Semi-local Features for Non-rigid Shapes

Alexander M. Bronstein, Michael M. Bronstein, Roee Litman, 2013, Innovations for Shape Analysis, Models and Algorithms.

Stable volumetric features in deformable shapes

Alexander M. Bronstein, Michael M. Bronstein, Roee Litman, 2012, Comput. Graph..

Sparse similarity-preserving hashing pdf

Guillermo Sapiro, Alexander M. Bronstein, Jonathan Masci, 2013, ICLR.

Nonisometric Surface Registration via Conformal Laplace–Beltrami Basis Pursuit pdf

Michael M. Bronstein, Rongjie Lai, Stefan C. Schonsheck, 2018, Journal of Scientific Computing.

Geometric Deep Learning: Going beyond Euclidean data

Pierre Vandergheynst, Joan Bruna, Yann LeCun, 2016, IEEE Signal Process. Mag..

Symmetries of non-rigid shapes

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation

Michael M. Bronstein, Ramunas Girdziusas, Davide Boscaini, 2014, 3DOR@Eurographics.

Intrinsic Regularity Detection in 3D Geometry

Niloy J. Mitra, Alexander M. Bronstein, Michael M. Bronstein, 2010, ECCV.

Shortest Paths and Fast Marching Methods

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, 2008 .

Shape Recognition with Spectral Distances

Alexander M. Bronstein, Michael M. Bronstein, A. Bronstein, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Separation of reflections via sparse ICA

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

Multigrid multidimensional scaling

Alexander M. Bronstein, Ron Kimmel, Irad Yavneh, 2006, Numer. Linear Algebra Appl..

Robust Expression-Invariant Face Recognition from Partially Missing Data

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2006, ECCV.

SHREC 2010: robust correspondence benchmark

Leonidas J. Guibas, Maks Ovsjanikov, Radu Horaud, 2010 .

BLOCK-COORDINATE RELATIVE NEWTON METHOD FOR BLIND SOURCE SEPARATION

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2003 .

Parallel algorithms for approximation of distance maps on parametric surfaces

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2008, TOGS.

New achievements in 3D hand shape recognition

Michael M. Bronstein, Jan Svoboda, 2018 .

Biometrics was no match for hair-raising tricks

Alexander M. Bronstein, Michael M. Bronstein, 2002, Nature.

Quasi-maximum likelihood blind deconvolution of images acquired through scattering media

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2004, 2004 2nd IEEE International Symposium on Biomedical Imaging: Nano to Macro (IEEE Cat No. 04EX821).

On reconstruction of non-rigid shapes with intrinsic regularization

Alexander M. Bronstein, Ron Kimmel, Guy Rosman, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Story of Cinderella

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, 2007 .

Multimodal Manifold Analysis by Simultaneous Diagonalization of Laplacians

Davide Eynard, Alexander M. Bronstein, Michael M. Bronstein, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Are MSER Features Really Interesting?

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.

SHREC '11: Robust Feature Detection and Description Benchmark pdf

Radu Horaud, Paul Suetens, Alexander M. Bronstein, 2011, 3DOR@Eurographics.

Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting pdf

Stefanos Zafeiriou, Michael M. Bronstein, Fabrizio Frasca, 2020, ArXiv.

RecSys 2020 Challenge Workshop: Engagement Prediction on Twitter’s Home Timeline

Nazareno Andrade, Michael M. Bronstein, Alykhan Tejani, 2020, RecSys.

Computer Vision - ECCV 2014 Workshops

Gerhard Goos, Juris Hartmanis, Jan van Leeuwen, 2014, Lecture Notes in Computer Science.

Jürgen Schmidhuber, Alexander M. Bronstein, Jonathan Masci, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Geodesic Convolutional Neural Networks on Riemannian Manifolds

Pierre Vandergheynst, Jonathan Masci, Michael M. Bronstein, 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).

Blind source separation using block-coordinate relative Newton method

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2004, Signal Process..

Asymptotic metrics on the space of matrices under the commutation relation pdf

Michael M. Bronstein, Klaus Glashoff, 2013, ArXiv.

Sparse ICA for blind separation of transmitted and reflected images

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2005, Int. J. Imaging Syst. Technol..

Expression-Invariant Representations of Faces

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2007, IEEE Transactions on Image Processing.

Graph Attentional Autoencoder for Anticancer Hyperfood Prediction pdf

Michael M. Bronstein, Ivan Laponogov, Kirill A. Veselkov, 2020, ArXiv.

Fusion of 2D and 3D data in three-dimensional face recognition

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

Almost-commuting matrices are almost jointly diagonalizable pdf

Michael M. Bronstein, Klaus Glashoff, M. Bronstein, 2013, ArXiv.

Shape‐from‐Operator: Recovering Shapes from Intrinsic Operators

Davide Eynard, Michael M. Bronstein, Davide Boscaini, 2015, Comput. Graph. Forum.

Reconstruction in diffraction ultrasound tomography using nonuniform FFT

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2002, IEEE Transactions on Medical Imaging.

Localized Manifold Harmonics for Spectral Shape Analysis

Michael M. Bronstein, Umberto Castellani, Simone Melzi, 2017, Comput. Graph. Forum.

Computer Vision - ECCV 2014 Workshops

Lourdes Agapito, Carsten Rother, Michael M. Bronstein, 2014, Lecture Notes in Computer Science.

Efficient Deformable Shape Correspondence via Kernel Matching

Daniel Cremers, Alexander M. Bronstein, Michael M. Bronstein, 2017, 2017 International Conference on 3D Vision (3DV).

Deformable Shape Retrieval by Learning Diffusion Kernels

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2011, SSVM.

PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks pdf

Leonidas J. Guibas, Jonathan Masci, Michael M. Bronstein, 2018, ICLR.

Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation

Stefanos Zafeiriou, Michael M. Bronstein, Stylianos Ploumpis, 2019, 2019 IEEE/CVF International Conference on Computer Vision (ICCV).

Scale Space and Variational Methods in Computer Vision

Alfred M. Bruckstein, Alexander M. Bronstein, Michael M. Bronstein, 2011, Lecture Notes in Computer Science.

Nonlinear Dimensionality Reduction by Topologically Constrained Isometric Embedding

Alexander M. Bronstein, Ron Kimmel, Guy Rosman, 2010, International Journal of Computer Vision.

Fake News Detection on Social Media using Geometric Deep Learning pdf

Davide Eynard, Michael M. Bronstein, Fabrizio Frasca, 2019, ArXiv.

Calculus of Nonrigid Surfaces for Geometry and Texture Manipulation

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2007, IEEE Transactions on Visualization and Computer Graphics.

Partial Matching of Deformable Shapes

Daniel Cremers, Andrea Torsello, Michael M. Bronstein, 2016, 3DOR@Eurographics.

"Unmixing" tissues: sparse component analysis in multi-contrast MRI

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2005, IEEE International Conference on Image Processing 2005.

Computing and processing correspondences with functional maps

Leonidas J. Guibas, Maks Ovsjanikov, Frédéric Chazal, 2016, SIGGRAPH Courses.

Spatial Maps: From Low Rank Spectral to Sparse Spatial Functional Representations

Andrea Torsello, Michael M. Bronstein, Andrea Gasparetto, 2017, 2017 International Conference on 3D Vision (3DV).

Blind Deconvolution Using the Relative Newton Method

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2004, ICA.

Utilising Graph Machine Learning within Drug Discovery and Development pdf

Jian Tang, Michael M. Bronstein, Jyothish Soman, 2020, ArXiv.

Fully Spectral Partial Shape Matching

Alexander M. Bronstein, Michael M. Bronstein, Emanuele Rodolà, 2017, Comput. Graph. Forum.

Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment

Alexander M. Bronstein, Andrea Cerri, Silvia Biasotti, 2016, Comput. Graph. Forum.

SHREC 2010: robust large-scale shape retrieval benchmark

Iasonas Kokkinos, Leonidas J. Guibas, Maks Ovsjanikov, 2010 .

Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics

Robert J. Wood, Michael M. Bronstein, Shane Gero, 2019, Scientific Reports.

Subspace Least Squares Multidimensional Scaling pdf

Alexander M. Bronstein, Michael M. Bronstein, Amit Boyarski, 2017, SSVM.

Quantifying 3D Shape Similarity Using Maps: Recent Trends, Applications and Perspectives

Alexander M. Bronstein, Andrea Cerri, Silvia Biasotti, 2014, Eurographics.

Non‐Rigid Puzzles

Daniel Cremers, Alexander M. Bronstein, Michael M. Bronstein, 2016, Comput. Graph. Forum.

Shape-from-intrinsic operator pdf

Davide Eynard, Michael M. Bronstein, Davide Boscaini, 2014, ArXiv.

Quasi maximum likelihood MIMO blind deconvolution: Super- and sub-Gaussianity versus consistency

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2005, IEEE Transactions on Signal Processing.

Relative optimization for blind deconvolution

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2005, IEEE Transactions on Signal Processing.

Publisher Correction: Deep Machine Learning Techniques for the Detection and Classification of Sperm Whale Bioacoustics

Robert J. Wood, Michael M. Bronstein, Shane Gero, 2019, Scientific Reports.

Rock, Paper, and Scissors: extrinsic vs. intrinsic similarity of non-rigid shapes

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Expression-Invariant 3D Face Recognition

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2003, AVBPA.

Geometric deep learning

Jonathan Masci, Michael M. Bronstein, Hao Li, 2016, SIGGRAPH ASIA Courses.

Spatially-Sensitive Affine-Invariant Image Descriptors

Alexander M. Bronstein, Michael M. Bronstein, A. Bronstein, 2010, ECCV.

Optimal nonlinear estimation of photon coordinates in PET

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

Shape Retrieval of Non-rigid 3D Human Models

Bo Li, Gary K. L. Tam, Ralph R. Martin, 2014, International Journal of Computer Vision.

Dual-Primal Graph Convolutional Networks pdf

Stephan Günnemann, Michael M. Bronstein, Aleksandar Bojchevski, 2018, ArXiv.

Fast geometric learning with symbolic matrices

Jean Feydy, Michael M. Bronstein, Benjamin Charlier, 2020, NeurIPS.

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs

Jonathan Masci, Michael M. Bronstein, Jan Svoboda, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Topology-Invariant Similarity of Nonrigid Shapes

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2009, International Journal of Computer Vision.

On Separation of Semitransparent Dynamic Images from Static Background

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2006, ICA.

Dynamic Graph CNN for Learning on Point Clouds

Yue Wang, Michael M. Bronstein, Ziwei Liu, 2018, ACM Trans. Graph..

GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching

Federico Tombari, Michael M. Bronstein, Luigi Di Stefano, 2019, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Three-Dimensional Face Recognition

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2005, International Journal of Computer Vision.

Submitted for Review to Ieee Transactions on Image Processing Blind Deconvolution of Images Using Optimal Sparse Representations

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2022 .

Intel® RealSense™ SR300 Coded Light Depth Camera

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

ShapeNet: Convolutional Neural Networks on Non-Euclidean Manifolds pdf

Pierre Vandergheynst, Jonathan Masci, Michael M. Bronstein, 2015, ArXiv.

Kernel Functional Maps

Michael M. Bronstein, Justin Solomon, Larry Wang, 2018, Comput. Graph. Forum.

Coupled quasi‐harmonic bases

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2012, Comput. Graph. Forum.

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

Xavier Bresson, Michael M. Bronstein, Federico Monti, 2017, NIPS.

Graph Neural Networks for IceCube Signal Classification

Prabhat, Joan Bruna, Zahra Ronaghi, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

Diffusion Geometry in Shape Analysis

Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, 2012, Eurographics.

Structure-preserving color transformations using Laplacian commutativity pdf

Davide Eynard, Michael M. Bronstein, Artiom Kovnatsky, 2013, ArXiv.

SHREC'10 Track: Robust Shape Retrieval

Iasonas Kokkinos, Leonidas J. Guibas, Maks Ovsjanikov, 2010, 3DOR@Eurographics.

3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties pdf

Peter Claes, Michael M. Bronstein, Mark D. Shriver, 2020, ArXiv.

Sparse Modeling of Intrinsic Correspondences

Guillermo Sapiro, Alexander M. Bronstein, Michael M. Bronstein, 2012, Comput. Graph. Forum.

Full and Partial Symmetries of Non-rigid Shapes

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2010, International Journal of Computer Vision.

Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II

Lourdes Agapito, Carsten Rother, Michael M. Bronstein, 2015 .

Computing and processing correspondences with functional maps

Leonidas J. Guibas, Maks Ovsjanikov, Frédéric Chazal, 2016, SIGGRAPH ASIA Courses.

Partial Single- and Multishape Dense Correspondence Using Functional Maps

Daniel Cremers, Alexander M. Bronstein, Michael M. Bronstein, 2018 .

Single Image 3D Hand Reconstruction with Mesh Convolutions pdf

Stefanos Zafeiriou, Michael M. Bronstein, Riza Alp Güler, 2019, BMVC.

Isometric Embedding of Facial Surfaces into

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2005, Scale-Space.

Equi-affine Invariant Geometries of Articulated Objects

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2011, Theoretical Foundations of Computer Vision.

Shape Google: a computer vision approach to isometry invariant shape retrieval

Leonidas J. Guibas, Maks Ovsjanikov, Alexander M. Bronstein, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Equi-affine Invariant Geometry for Shape Analysis

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2013, Journal of Mathematical Imaging and Vision.

Computer Vision - ECCV 2014 Workshops

Gerhard Goos, Juris Hartmanis, Jan van Leeuwen, 2014, Lecture Notes in Computer Science.

Facetoface: An Isometric Model for Facial Animation

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2006, AMDO.

CAYLEYNETS: SPECTRAL GRAPH CNNS WITH COMPLEX RATIONAL FILTERS

Xavier Bresson, Michael M. Bronstein, Ron Levie, 2018 .

Affine-invariant geodesic geometry of deformable 3D shapes

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2010, Comput. Graph..

Kernel diff-hash pdf

Michael M. Bronstein, M. Bronstein, 2011, ArXiv.

The Video Genome pdf

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2010, ArXiv.

Face 2 face 2 : An isometric model for facial animation

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, 2006 .

THE NON-UNIFORM FFT AND SOME OF ITS APPLICATIONS

Alexander M. Bronstein, Michael M. Bronstein, A. Bronstein, 2002 .

Deformable Shape Retrieval with Missing Parts

Duc Anh Duong, Alexandre Boulch, Minh N. Do, 2017, 3DOR@Eurographics.

Expression-invariant face recognition via spherical embedding

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2005, IEEE International Conference on Image Processing 2005.

CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters

Xavier Bresson, Michael M. Bronstein, Ron Levie, 2017, IEEE Transactions on Signal Processing.

Deep Functional Maps: Structured Prediction for Dense Shape Correspondence

Alexander M. Bronstein, Michael M. Bronstein, Emanuele Rodolà, 2017, 2017 IEEE International Conference on Computer Vision (ICCV).

High-Resolution Structured Light Range Scanner with Automatic Calibration

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, 2003 .

Photometric Heat Kernel Signatures

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2011, SSVM.

Iterative reconstruction in diffraction tomography using nonuniform fast Fourier transform

Alexander M. Bronstein, Michael M. Bronstein, Michael Zibulevsky, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

Alfred M. Bruckstein, Alexander M. Bronstein, Ron Kimmel, 2009, International Journal of Computer Vision.

Expression-invariant 3D face recognition

Michael M. Bronstein, 2008 .

Optimal sparse representations for blind source separation and blind deconvolution: a learning approach

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

Contactless biometric hand geometry recognition using a low-cost 3D camera

Michael M. Bronstein, Martin Drahanský, Jan Svoboda, 2015, 2015 International Conference on Biometrics (ICB).

BLIND SEPARATION OF REFLECTIONS USING SPARSE ICA

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2003 .

Shape google: Geometric words and expressions for invariant shape retrieval

Leonidas J. Guibas, Maks Ovsjanikov, Alexander M. Bronstein, 2011, TOGS.

Separation of semireflective layers using sparse ICA

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

Shape Analysis with Anisotropic Windowed Fourier Transform

Michael M. Bronstein, Umberto Castellani, Simone Melzi, 2016, 2016 Fourth International Conference on 3D Vision (3DV).

Generative convolutional networks for latent fingerprint reconstruction

Michael M. Bronstein, Jan Svoboda, Federico Monti, 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).

Functional correspondence by matrix completion

Xavier Bresson, Pierre Vandergheynst, Michael M. Bronstein, 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Fast relative Newton algorithm for blind deconvolution of images

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

Scale-invariant heat kernel signatures for non-rigid shape recognition

Iasonas Kokkinos, Michael M. Bronstein, M. Bronstein, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Group-Valued Regularization for Analysis of Articulated Motion

Alexander M. Bronstein, Ron Kimmel, Guy Rosman, 2012, ECCV Workshops.

Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild

Iasonas Kokkinos, Stefanos Zafeiriou, Michael M. Bronstein, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Coupled Functional Maps

Davide Eynard, Michael M. Bronstein, Emanuele Rodolà, 2016, 2016 Fourth International Conference on 3D Vision (3DV).

Deep Geometric Matrix Completion: A New Way for Recommender Systems

Xavier Bresson, Michael M. Bronstein, Federico Monti, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Geometrically Principled Connections in Graph Neural Networks

Stefanos Zafeiriou, Michael M. Bronstein, Shunwang Gong, 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Not only size matters: Regularized partial matching of nonrigid shapes

Alexander M. Bronstein, Michael M. Bronstein, A. Bronstein, 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

SHREC'10 Track: Feature Detection and Description

Iasonas Kokkinos, Leonidas J. Guibas, Maks Ovsjanikov, 2010, 3DOR@Eurographics.

Group-Valued Regularization for Motion Segmentation of Articulated Shapes

Alon Wolf, Alexander M. Bronstein, Ron Kimmel, 2013, Innovations for Shape Analysis, Models and Algorithms.

Learning class‐specific descriptors for deformable shapes using localized spectral convolutional networks

Pierre Vandergheynst, Jonathan Masci, Michael M. Bronstein, 2015, SGP '15.

Weighted distance maps computation on parametric three-dimensional manifolds

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2007, J. Comput. Phys..

Intrinsic shape context descriptors for deformable shapes

Iasonas Kokkinos, Alexander M. Bronstein, Michael M. Bronstein, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Articulated Motion Segmentation of Point Clouds by Group-Valued Regularization

Alexander M. Bronstein, Ron Kimmel, Guy Rosman, 2012, 3DOR@Eurographics.

The Average Mixing Kernel Signature

Andrea Torsello, Michael M. Bronstein, Luca Cosmo, 2020, ECCV.

Lazy Sliding Window Implementation of the Bilateral Filter on Parallel Architectures

Michael M. Bronstein, M. Bronstein, 2011, IEEE Transactions on Image Processing.

Face Recognition from Facial Surface Metric

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2004, ECCV.

Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation pdf

Feng Liu, Stefanos Zafeiriou, Michael M. Bronstein, 2020, International Journal of Computer Vision.

Shape Retrieval of Non-Rigid 3D Human Models

Bo Li, Ralph R. Martin, Andrea Giachetti, 2014, 3DOR@Eurographics.

SIMD implementation of the bilateral filter

Michael M. Bronstein, 2009 .

Deep Learning for Computer Graphics and Geometry Processing

Iasonas Kokkinos, Leonidas J. Guibas, Niloy J. Mitra, 2019, Eurographics.

A Gromov-Hausdorff Framework with Diffusion Geometry for Topologically-Robust Non-rigid Shape Matching

Guillermo Sapiro, Alexander M. Bronstein, Ron Kimmel, 2010, International Journal of Computer Vision.

Learnable low rank sparse models for speech denoising

Guillermo Sapiro, Alexander M. Bronstein, Michael M. Bronstein, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

New Results - Fusion/Registration

Ben Glocker, Nikos Komodakis, Nikos Paragios, 2011 .

Interactive Curve Constrained Functional Maps

Leif Kobbelt, Michael M. Bronstein, Justin Solomon, 2018, Comput. Graph. Forum.

Anisotropic Diffusion Descriptors

Daniel Cremers, Jonathan Masci, Michael M. Bronstein, 2016, Comput. Graph. Forum.

3D-color video camera

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014 Proceedings, Part IV

Lourdes Agapito, Carsten Rother, Michael M. Bronstein, 2015 .

Multimodal diff-hash pdf

Michael M. Bronstein, 2011, ArXiv.

Diffusion framework for geometric and photometric data fusion in non-rigid shape analysis pdf

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2011, ArXiv.

Topologically Constrained Isometric Embedding

Alexander M. Bronstein, Ron Kimmel, Guy Rosman, 2006, Human Motion.

Structure from Motion Using Augmented Lagrangian Robust Factorization

Michael M. Bronstein, Klaus Glashoff, M. Bronstein, 2012, 2012 Second International Conference on 3D Imaging, Modeling, Processing, Visualization & Transmission.

Functional Maps Representation On Product Manifolds

Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon, 2018, Comput. Graph. Forum.

Joint intrinsic and extrinsic similarity for recognition of non-rigid shapes

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, 2007 .

Affine-invariant diffusion geometry for the analysis of deformable 3D shapes

Alexander M. Bronstein, Michael M. Bronstein, Dan Raviv, 2010, CVPR 2011.

New Results - Shape, Landmark & Image-based Deformable Registration

Ben Glocker, Nikos Paragios, Christos Davatzikos, 2009 .

Discrete Minimum Distortion Correspondence Problems for Non-rigid Shape Matching

Nikos Paragios, Alexander M. Bronstein, Michael M. Bronstein, 2011, SSVM.

SHREC'10 Track: Correspondence Finding

Leonidas J. Guibas, Maks Ovsjanikov, Radu Horaud, 2010, 3DOR@Eurographics.

Manifold Intrinsic Similarity

Alexander M. Bronstein, Michael M. Bronstein, A. Bronstein, 2015, Handbook of Mathematical Methods in Imaging.

MOTIFNET: A MOTIF-BASED GRAPH CONVOLUTIONAL NETWORK FOR DIRECTED GRAPHS

Michael M. Bronstein, Federico Monti, Karl Otness, 2018, 2018 IEEE Data Science Workshop (DSW).

Numerical Geometry of Non-Rigid Shapes

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2009, Monographs in Computer Science.

Descriptor Learning for Omnidirectional Image Matching

Jürgen Schmidhuber, Jonathan Masci, Michael M. Bronstein, 2011, Registration and Recognition in Images and Videos.

QML Blind Deconvolution: Asymptotic Analysis

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2004, ICA.

Tuning Word2vec for Large Scale Recommendation Systems

Michael M. Bronstein, Dan Shiebler, Suvash Sedhain, 2020, RecSys.

Deep Learning for Shape Analysis

Jonathan Masci, Michael M. Bronstein, Evangelos Kalogerakis, 2016, Eurographics.

Group-Valued Regularization Framework for Motion Segmentation of Dynamic Non-rigid Shapes

Alon Wolf, Alexander M. Bronstein, Ron Kimmel, 2011, SSVM.

Partial Functional Correspondence

Daniel Cremers, Andrea Torsello, Michael M. Bronstein, 2017 .

Diffusion-geometric maximally stable component detection in deformable shapes pdf

Alexander M. Bronstein, Michael M. Bronstein, Roee Litman, 2010, Comput. Graph..

Transferability of Spectral Graph Convolutional Neural Networks pdf

Gitta Kutyniok, Michael M. Bronstein, Ron Levie, 2019, J. Mach. Learn. Res..

Separation of reflections via sparse ICA

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2003, SPIE Optics + Photonics.

Making Laplacians commute pdf

Michael M. Bronstein, Klaus Glashoff, Terry A. Loring, 2013, ArXiv.

Feature-Based Methods in 3D Shape Analysis

Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, 2012, 3D Imaging, Analysis and Applications.

Manifold Analysis by Topologically Constrained Isometric Embedding

Alexander M. Bronstein, Guy Rosman, Michael M. Bronstein, 2008 .

Matrix Completion on Graphs pdf

Xavier Bresson, Pierre Vandergheynst, Michael M. Bronstein, 2014, NIPS 2014.

Heat kernel coupling for multiple graph analysis pdf

Michael M. Bronstein, Klaus Glashoff, M. Bronstein, 2013, ArXiv.

Deformable Shape Completion with Graph Convolutional Autoencoders

Alexander M. Bronstein, Michael M. Bronstein, Or Litany, 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

Shape Correspondence with Isometric and Non-Isometric Deformations

Gary K. L. Tam, Daniel Cremers, Mathieu Aubry, 2019, 3DOR@Eurographics.

Sparse Models for Intrinsic Shape Correspondence

Guillermo Sapiro, Alexander M. Bronstein, Michael M. Bronstein, 2016, Perspectives in Shape Analysis.

Numerical Geometry of Non-Rigid Shapes, Monographs in Computer Science

Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, 2009 .

Gamut mapping with image Laplacian commutators

Davide Eynard, Michael M. Bronstein, Artiom Kovnatsky, 2014, 2014 IEEE International Conference on Image Processing (ICIP).

Computer Vision - ECCV 2014 Workshops

Gerhard Goos, Juris Hartmanis, Jan van Leeuwen, 2014, Lecture Notes in Computer Science.

Scalable resource allocation for H.264 video encoder: Frame-level controller

Michael M. Bronstein, 2009 .

Blind separation of tissues in multi-modal MRI using Sparse Component Analysis

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2005, 2005 13th European Signal Processing Conference.

Efficient Computation of Isometry-Invariant Distances Between Surfaces

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2006, SIAM J. Sci. Comput..

Alfred M. Bruckstein, Alexander M. Bronstein, Ron Kimmel, 2007, SSVM.

Regularized Partial Matching of Rigid Shapes

Alexander M. Bronstein, Michael M. Bronstein, A. Bronstein, 2008, ECCV.

Improved Functional Mappings via Product Preservation

Maks Ovsjanikov, Dorian Nogneng, Michael M. Bronstein, 2018, Comput. Graph. Forum.

Learning interpretable disease self-representations for drug repositioning pdf

Michael M. Bronstein, Ivan Laponogov, Fabrizio Frasca, 2019, ArXiv.

Supervised learning of bag‐of‐features shape descriptors using sparse coding

Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani, 2014, Comput. Graph. Forum.

Boosted metric learning for 3D multi-modal deformable registration

Nikos Paragios, Alexander M. Bronstein, Michael M. Bronstein, 2011, 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Palmprint recognition via discriminative index learning

Jonathan Masci, Michael M. Bronstein, Jan Svoboda, 2016, 2016 23rd International Conference on Pattern Recognition (ICPR).

Quasi Maximum Likelihood Blind Deconvolution of Images Using Optimal Sparse Representations

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2003 .

Efficient Globally Optimal 2D-to-3D Deformable Shape Matching

Daniel Cremers, Michael M. Bronstein, Zorah Lähner, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Robust Principal Component Analysis on Graphs

Xavier Bresson, Pierre Vandergheynst, Michael M. Bronstein, 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

MADMM: A Generic Algorithm for Non-smooth Optimization on Manifolds

Michael M. Bronstein, Klaus Glashoff, Artiom Kovnatsky, 2015, ECCV.

MeshGAN: Non-linear 3D Morphable Models of Faces pdf

Stefanos Zafeiriou, Yuxiang Zhou, Maja Pantic, 2019, ArXiv.

Data fusion through cross-modality metric learning using similarity-sensitive hashing

Nikos Paragios, Alexander M. Bronstein, Michael M. Bronstein, 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

Learning shape correspondence with anisotropic convolutional neural networks

Jonathan Masci, Michael M. Bronstein, Emanuele Rodolà, 2016, NIPS.

Laplacian colormaps: a framework for structure‐preserving color transformations

Davide Eynard, Michael M. Bronstein, Artiom Kovnatsky, 2014, Comput. Graph. Forum.

Stable Spectral Mesh Filtering

Alexander M. Bronstein, Michael M. Bronstein, Artiom Kovnatsky, 2012, ECCV Workshops.

Isospectralization, or How to Hear Shape, Style, and Correspondence

Maks Ovsjanikov, Michael M. Bronstein, Luca Cosmo, 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Multimodal diffusion geometry by joint diagonalization of Laplacians pdf

Davide Eynard, Alexander M. Bronstein, Michael M. Bronstein, 2012, ArXiv.

ncRNA Classification with Graph Convolutional Networks pdf

Pietro Liò, Michael M. Bronstein, Emanuele Rossi, 2019, ArXiv.

Matching of Deformable Shapes with Topological Noise

Daniel Cremers, Reinhard Klein, Michael M. Bronstein, 2016, 3DOR@Eurographics.

GRAND: Graph Neural Diffusion pdf

Michael M. Bronstein, Benjamin Paul Chamberlain, Maria I. Gorinova, 2021, ICML.

Understanding over-squashing and bottlenecks on graphs via curvature pdf

Michael M. Bronstein, Benjamin Paul Chamberlain, Jake Topping, 2021, ArXiv.

3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties

Michael M. Bronstein, Peter Claes, Mark D. Shriver, 2020, 2020 25th International Conference on Pattern Recognition (ICPR).

Equivariant Subgraph Aggregation Networks pdf

Michael M. Bronstein, Derek Lim, Fabrizio Frasca, 2021, ArXiv.

Partition and Code: learning how to compress graphs pdf

Michael M. Bronstein, Andreas Loukas, Giorgos Bouritsas, 2021, NeurIPS.

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges pdf

Joan Bruna, Michael M. Bronstein, Taco Cohen, 2021, ArXiv.

GReS: Workshop on Graph Neural Networks for Recommendation and Search

Jean-Michel Renders, Michael M. Bronstein, Stéphane Clinchant, 2021, RecSys.

Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales pdf

Robert J. Wood, Shafi Goldwasser, Antonio Torralba, 2021, ArXiv.

Expression-invariant three-dimensional face recognition

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2005 .

Feature-based image alignment via coupled Hough transforms

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2009 .

Optimal non-linear line-of-flight estimation in positron emission tomography

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2002, The 22nd Convention on Electrical and Electronics Engineers in Israel, 2002..

WaldHash: sequential similarity-preserving hashing

Maks Ovsjanikov, Alexander M. Bronstein, Michael M. Bronstein, 2010 .

An Isometric Model for Facial Animation

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, .

Partial matching of rigid shapes

Alexander M. Bronstein, Michael M. Bronstein, 2008 .

Optimization on the biorthogonal manifold

Michael M. Bronstein, Klaus Glashoff, 2016 .

In the Rigid Kingdom

Alexander M. Bronstein, Ron Kimmel, Michael M. Bronstein, 2008 .

Alfred M. Bruckstein, Alexander M. Bronstein, Ron Kimmel, 2007 .

Wassertein Barycenter and its Applications to Texture Mixing

Alfred M. Bruckstein, Alexander M. Bronstein, Michael M. Bronstein, 2012 .

Attributed Random Walk as Matrix Factorization

Michael M. Bronstein, Lei Chen, Shunwang Gong, 2019 .

Fast Multidimensional Scaling using Vector Extrapolation

Alexander M. Bronstein, Ron Kimmel, Guy Rosman, 2008 .

Optimal nonlinear line-of-flight estimation in positron emission tomography

Yehoshua Y. Zeevi, Alexander M. Bronstein, Michael M. Bronstein, 2003 .

Embedded System for 3 D Shape Reconstruction

Alexander M. Bronstein, Raja Giryes, Michael M. Bronstein, 2008 .