Google
Google Scholar
Semantic Scholar
MS Academic
CiteSeerX
ORCIDMichael M. Bronstein
Person information
- affiliation: Imperial College London, Department of Computing, IK
- affiliation: Technion - Israel Institute of Technology, Haifa, Israel
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2020
[j53]Aviad Zabatani
, Vitaly Surazhsky, Erez Sperling, Sagi Ben-Moshe, Ohad Menashe, David H. Silver, Zachi Karni, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel:
Intel® RealSense™ SR300 Coded Light Depth Camera. IEEE Trans. Pattern Anal. Mach. Intell. 42(10): 2333-2345 (2020)- [c106]Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou:
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild. CVPR 2020: 4989-4999 - [c105]Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou:
Geometrically Principled Connections in Graph Neural Networks. CVPR 2020: 11412-11421 - [c104]Vito Walter Anelli, Amra Delic, Gabriele Sottocornola, Jessie Smith, Nazareno Andrade, Luca Belli, Michael M. Bronstein, Akshay Gupta, Sofia Ira Ktena, Alexandre Lung-Yut-Fong, Frank Portman, Alykhan Tejani, Yuanpu Xie, Xiao Zhu, Wenzhe Shi:
RecSys 2020 Challenge Workshop: Engagement Prediction on Twitter's Home Timeline. RecSys 2020: 623-627 - [c103]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. RecSys 2020: 732-737 - [i65]Guadalupe Gonzalez, Shunwang Gong, Ivan Laponogov, Kirill A. Veselkov, Michael M. Bronstein:
Graph Attentional Autoencoder for Anticancer Hyperfood Prediction. CoRR abs/2001.05724 (2020) - [i64]Anees Kazi, Luca Cosmo, Nassir Navab, Michael M. Bronstein:
Differentiable Graph Module (DGM) Graph Convolutional Networks. CoRR abs/2002.04999 (2020) - [i63]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, Long Lai, Bo Li, Chunyuan Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye:
Shape retrieval of non-rigid 3d human models. CoRR abs/2003.08763 (2020) - [i62]Luca Cosmo, Anees Kazi, Seyed-Ahmad Ahmadi, Nassir Navab, Michael M. Bronstein:
Latent Patient Network Learning for Automatic Diagnosis. CoRR abs/2003.13620 (2020) - [i61]Dominik Kulon, Riza Alp Güler, Iasonas Kokkinos, Michael M. Bronstein, Stefanos Zafeiriou:
Weakly-Supervised Mesh-Convolutional Hand Reconstruction in the Wild. CoRR abs/2004.01946 (2020) - [i60]Shunwang Gong, Mehdi Bahri, Michael M. Bronstein, Stefanos Zafeiriou:
Geometrically Principled Connections in Graph Neural Networks. CoRR abs/2004.02658 (2020) - [i59]Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti:
SIGN: Scalable Inception Graph Neural Networks. CoRR abs/2004.11198 (2020) - [i58]Luca Belli, Sofia Ira Ktena, Alykhan Tejani, Alexandre Lung-Yut-Fong, Frank Portman, Xiao Zhu, Yuanpu Xie, Akshay Gupta, Michael M. Bronstein, Amra Delic, Gabriele Sottocornola, Vito Walter Anelli, Nazareno Andrade, Jessie Smith, Wenzhe Shi:
Privacy-Preserving Recommender Systems Challenge on Twitter's Home Timeline. CoRR abs/2004.13715 (2020) - [i57]Giorgos Bouritsas, Fabrizio Frasca, Stefanos Zafeiriou, Michael M. Bronstein:
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting. CoRR abs/2006.09252 (2020) - [i56]Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein:
Temporal Graph Networks for Deep Learning on Dynamic Graphs. CoRR abs/2006.10637 (2020) - [i55]Soha Sadat Mahdi, Nele Nauwelaers, Philip Joris, Giorgos Bouritsas, Shunwang Gong, Sergiy Bokhnyak, Susan Walsh, Mark D. Shriver, Michael M. Bronstein, Peter Claes:
3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties. CoRR abs/2009.04746 (2020)
2010 – 2019
- 2019
- [j52]Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps Representation On Product Manifolds. Comput. Graph. Forum 38(1): 678-689 (2019) - [j51]Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon:
Dynamic Graph CNN for Learning on Point Clouds. ACM Trans. Graph. 38(5): 146:1-146:12 (2019) - [j50]Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein:
CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters. IEEE Trans. Signal Process. 67(1): 97-109 (2019) - [c102]Roberto M. Dyke, C. Stride, Yu-Kun Lai, Paul L. Rosin, Mathieu Aubry, Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers, Matthew Fisher, Thibault Groueix, Daoliang Guo, Vladimir G. Kim, Ron Kimmel, Zorah Lähner, Kun Li, Or Litany, Tal Remez, Emanuele Rodolà, Bryan C. Russell, Yusuf Sahillioglu, Ron Slossberg, Gary K. L. Tam, Matthias Vestner, Z. Wu, Jingyu Yang:
Shape Correspondence with Isometric and Non-Isometric Deformations. 3DOR@Eurographics 2019: 111-119 - [c101]Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael M. Bronstein, Stefanos Zafeiriou:
Single Image 3D Hand Reconstruction with Mesh Convolutions. BMVC 2019: 45 - [c100]Simone Melzi, Riccardo Spezialetti, Federico Tombari, Michael M. Bronstein, Luigi di Stefano, Emanuele Rodolà:
GFrames: Gradient-Based Local Reference Frame for 3D Shape Matching. CVPR 2019: 4629-4638 - [c99]Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Isospectralization, or How to Hear Shape, Style, and Correspondence. CVPR 2019: 7529-7538 - [c98]Michael M. Bronstein, Leonidas J. Guibas, Iasonas Kokkinos, Or Litany, Niloy J. Mitra, Federico Monti, Emanuele Rodolà:
Deep Learning for Computer Graphics and Geometry Processing. Eurographics (Tutorials) 2019: 43 - [c97]Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Stefanos Zafeiriou, Michael M. Bronstein:
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation. ICCV 2019: 7212-7221 - [c96]Shunwang Gong, Lei Chen, Michael M. Bronstein, Stefanos Zafeiriou:
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator. ICCV Workshops 2019: 4141-4148 - [c95]Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas:
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. ICLR (Poster) 2019 - [i54]Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein:
Fake News Detection on Social Media using Geometric Deep Learning. CoRR abs/1902.06673 (2019) - [i53]Shiyang Cheng, Michael M. Bronstein, Yuxiang Zhou, Irene Kotsia, Maja Pantic, Stefanos Zafeiriou:
MeshGAN: Non-linear 3D Morphable Models of Faces. CoRR abs/1903.10384 (2019) - [i52]Dominik Kulon, Haoyang Wang, Riza Alp Güler, Michael M. Bronstein, Stefanos Zafeiriou:
Single Image 3D Hand Reconstruction with Mesh Convolutions. CoRR abs/1905.01326 (2019) - [i51]Giorgos Bouritsas, Sergiy Bokhnyak, Stylianos Ploumpis, Michael M. Bronstein, Stefanos Zafeiriou:
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and Generation. CoRR abs/1905.02876 (2019) - [i50]Emanuele Rossi, Federico Monti, Michael M. Bronstein, Pietro Liò:
ncRNA Classification with Graph Convolutional Networks. CoRR abs/1905.06515 (2019) - [i49]Ron Levie, Michael M. Bronstein, Gitta Kutyniok:
Transferability of Spectral Graph Convolutional Neural Networks. CoRR abs/1907.12972 (2019) - [i48]Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez, Ivan Laponogov, Kirill A. Veselkov, Alberto Paccanaro, Michael M. Bronstein:
Learning interpretable disease self-representations for drug repositioning. CoRR abs/1909.06609 (2019) - [i47]Shunwang Gong, Lei Chen, Michael M. Bronstein, Stefanos Zafeiriou:
SpiralNet++: A Fast and Highly Efficient Mesh Convolution Operator. CoRR abs/1911.05856 (2019) - 2018
- [j49]Dorian Nogneng, Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein, Maks Ovsjanikov:
Improved Functional Mappings via Product Preservation. Comput. Graph. Forum 37(2): 179-190 (2018) - [j48]Anne Gehre, Michael M. Bronstein, Leif Kobbelt, Justin Solomon:
Interactive Curve Constrained Functional Maps. Comput. Graph. Forum 37(5): 1-12 (2018) - [j47]Larry Wang, Anne Gehre, Michael M. Bronstein, Justin Solomon:
Kernel Functional Maps. Comput. Graph. Forum 37(5): 27-36 (2018) - [j46]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Localized Manifold Harmonics for Spectral Shape Analysis. Comput. Graph. Forum 37(6): 20-34 (2018) - [c94]Or Litany, Alexander M. Bronstein, Michael M. Bronstein, Ameesh Makadia:
Deformable Shape Completion With Graph Convolutional Autoencoders. CVPR 2018: 1886-1895 - [c93]Federico Monti, Karl Otness, Michael M. Bronstein:
MOTIFNET: A Motif-Based Graph Convolutional Network for Directed Graphs. DSW 2018: 225-228 - [c92]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Deep Geometric Matrix Completion: A New Way for Recommender Systems. ICASSP 2018: 6852-6856 - [c91]Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna:
Graph Neural Networks for IceCube Signal Classification. ICMLA 2018: 386-391 - [c90]Emanuele Rodolà, Zorah Lähner, Alex M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps on Product Manifolds. SGP (Posters) 2018: 9-10 - [i46]Yue Wang, Yongbin Sun, Ziwei Liu, Sanjay E. Sarma, Michael M. Bronstein, Justin M. Solomon:
Dynamic Graph CNN for Learning on Point Clouds. CoRR abs/1801.07829 (2018) - [i45]Federico Monti, Karl Otness, Michael M. Bronstein:
MotifNet: a motif-based Graph Convolutional Network for directed graphs. CoRR abs/1802.01572 (2018) - [i44]Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas:
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. CoRR abs/1806.00088 (2018) - [i43]Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein:
Dual-Primal Graph Convolutional Networks. CoRR abs/1806.00770 (2018) - [i42]Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna:
Graph Neural Networks for IceCube Signal Classification. CoRR abs/1809.06166 (2018) - [i41]Stefan C. Schonsheck, Michael M. Bronstein, Rongjie Lai:
Nonisometric Surface Registration via Conformal Laplace-Beltrami Basis Pursuit. CoRR abs/1809.07399 (2018) - [i40]Emanuele Rodolà, Zorah Lähner, Alexander M. Bronstein, Michael M. Bronstein, Justin Solomon:
Functional Maps Representation on Product Manifolds. CoRR abs/1809.10940 (2018) - [i39]Luca Cosmo, Mikhail Panine, Arianna Rampini, Maks Ovsjanikov, Michael M. Bronstein, Emanuele Rodolà:
Isospectralization, or how to hear shape, style, and correspondence. CoRR abs/1811.11465 (2018) - 2017
- [j45]Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers:
Partial Functional Correspondence. Comput. Graph. Forum 36(1): 222-236 (2017) - [j44]Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein:
Fully Spectral Partial Shape Matching. Comput. Graph. Forum 36(2): 247-258 (2017) - [j43]Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst:
Geometric Deep Learning: Going beyond Euclidean data. IEEE Signal Process. Mag. 34(4): 18-42 (2017) - [c89]Andrea Gasparetto, Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello:
Spatial Maps: From Low Rank Spectral to Sparse Spatial Functional Representations. 3DV 2017: 477-485 - [c88]Matthias Vestner, Zorah Lähner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. 3DV 2017: 517-526 - [c87]Emanuele Rodolà, Luca Cosmo, Or Litany, Michael M. Bronstein, Alexander M. Bronstein, Nicolas Audebert, A. Ben Hamza, Alexandre Boulch, Umberto Castellani, Minh N. Do, Duc Anh Duong, Takahiko Furuya, Andrea Gasparetto, Y. Hong, J. Kim, Bertrand Le Saux, Roee Litman, Majid Masoumi, Giorgia Minello, Hai-Dang Nguyen, V.-T. Nguyen, Ryutarou Ohbuchi, Viet-Khoi Pham, Thuyen V. Phan, M. Rezaei, Andrea Torsello, Minh-Triet Tran, Q. T. Tran, Bao Truong, L. Wan, Changqing Zou:
Deformable Shape Retrieval with Missing Parts. 3DOR@Eurographics 2017 - [c86]Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein:
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs. CVPR 2017: 5425-5434 - [c85]Jan Svoboda, Federico Monti, Michael M. Bronstein:
Generative convolutional networks for latent fingerprint reconstruction. IJCB 2017: 429-436 - [c84]Or Litany, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein:
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence. ICCV 2017: 5660-5668 - [c83]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. NIPS 2017: 3697-3707 - [c82]Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein:
Subspace Least Squares Multidimensional Scaling. SSVM 2017: 681-693 - [c81]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Localized Manifold Harmonics for Spectral Shape Analysis. SGP (Posters) 2017: 5-6 - [c80]Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein:
Computing and processing correspondences with functional maps. SIGGRAPH Courses 2017: 5:1-5:62 - [i38]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. CoRR abs/1704.06803 (2017) - [i37]Or Litany, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein:
Deep Functional Maps: Structured Prediction for Dense Shape Correspondence. CoRR abs/1704.08686 (2017) - [i36]Jan Svoboda, Federico Monti, Michael M. Bronstein:
Generative Convolutional Networks for Latent Fingerprint Reconstruction. CoRR abs/1705.01707 (2017) - [i35]Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein:
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters. CoRR abs/1705.07664 (2017) - [i34]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Localized Manifold Harmonics for Spectral Shape Analysis. CoRR abs/1707.02596 (2017) - [i33]Zorah Lähner, Matthias Vestner, Amit Boyarski, Or Litany, Ron Slossberg, Tal Remez, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Ron Kimmel, Daniel Cremers:
Efficient Deformable Shape Correspondence via Kernel Matching. CoRR abs/1707.08991 (2017) - [i32]Amit Boyarski, Alexander M. Bronstein, Michael M. Bronstein:
Subspace Least Squares Multidimensional Scaling. CoRR abs/1709.03484 (2017) - [i31]Or Litany, Alexander M. Bronstein, Michael M. Bronstein, Ameesh Makadia:
Deformable Shape Completion with Graph Convolutional Autoencoders. CoRR abs/1712.00268 (2017) - 2016
- [j42]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers:
Anisotropic Diffusion Descriptors. Comput. Graph. Forum 35(2): 431-441 (2016) - [j41]Or Litany, Emanuele Rodolà, Alexander M. Bronstein, Michael M. Bronstein, Daniel Cremers:
Non-Rigid Puzzles. Comput. Graph. Forum 35(5): 135-143 (2016) - [j40]Silvia Biasotti, Andrea Cerri, Alexander M. Bronstein, Michael M. Bronstein:
Recent Trends, Applications, and Perspectives in 3D Shape Similarity Assessment. Comput. Graph. Forum 35(6): 87-119 (2016) - [j39]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, L. Lai, Bo Li, Chen-Feng Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Li Sun, Gary K. L. Tam, Atsushi Tatsuma, Jianbo Ye:
Shape Retrieval of Non-rigid 3D Human Models. Int. J. Comput. Vis. 120(2): 169-193 (2016) - [c79]Luca Cosmo, Emanuele Rodolà, Jonathan Masci, Andrea Torsello, Michael M. Bronstein:
Matching Deformable Objects in Clutter. 3DV 2016: 1-10 - [c78]Davide Eynard, Emanuele Rodolà, Klaus Glashoff, Michael M. Bronstein:
Coupled Functional Maps. 3DV 2016: 399-407 - [c77]Simone Melzi, Emanuele Rodolà, Umberto Castellani, Michael M. Bronstein:
Shape Analysis with Anisotropic Windowed Fourier Transform. 3DV 2016: 470-478 - [c76]Luca Cosmo, Emanuele Rodolà, Michael M. Bronstein, Andrea Torsello, Daniel Cremers, Yusuf Sahillioglu:
Partial Matching of Deformable Shapes. 3DOR@Eurographics 2016 - [c75]Zorah Lähner, Emanuele Rodolà, Michael M. Bronstein, Daniel Cremers, Oliver Burghard, Luca Cosmo, Alexander Dieckmann, Reinhard Klein, Yusuf Sahillioglu:
Matching of Deformable Shapes with Topological Noise. 3DOR@Eurographics 2016 - [c74]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CVPR 2016: 2185-2193 - [c73]Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein:
MADMM: A Generic Algorithm for Non-smooth Optimization on Manifolds. ECCV (5) 2016: 680-696 - [c72]Michael M. Bronstein, Evangelos Kalogerakis, Emanuele Rodolà, Jonathan Masci, Davide Boscaini:
Deep Learning for Shape Analysis. Eurographics (Tutorials) 2016 - [c71]Jan Svoboda, Jonathan Masci, Michael M. Bronstein:
Palmprint recognition via discriminative index learning. ICPR 2016: 4232-4237 - [c70]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein:
Learning shape correspondence with anisotropic convolutional neural networks. NIPS 2016: 3189-3197 - [c69]Jonathan Masci, Emanuele Rodolà, Davide Boscaini, Michael M. Bronstein, Hao Li:
Geometric deep learning. SIGGRAPH ASIA Courses 2016: 1:1-1:50 - [c68]Maks Ovsjanikov, Etienne Corman, Michael M. Bronstein, Emanuele Rodolà, Mirela Ben-Chen, Leonidas J. Guibas, Frédéric Chazal, Alexander M. Bronstein:
Computing and processing correspondences with functional maps. SIGGRAPH ASIA Courses 2016: 9:1-9:60 - [p5]Jonathan Pokrass, Alexander M. Bronstein, Michael M. Bronstein, Pablo Sprechmann, Guillermo Sapiro:
Sparse Models for Intrinsic Shape Correspondence. Perspectives in Shape Analysis 2016: 211-230 - [i30]Zorah Lähner, Emanuele Rodolà, Frank R. Schmidt, Michael M. Bronstein, Daniel Cremers:
Efficient Globally Optimal 2D-to-3D Deformable Shape Matching. CoRR abs/1601.06070 (2016) - [i29]Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Michael M. Bronstein:
Learning shape correspondence with anisotropic convolutional neural networks. CoRR abs/1605.06437 (2016) - [i28]Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, Pierre Vandergheynst:
Geometric deep learning: going beyond Euclidean data. CoRR abs/1611.08097 (2016) - [i27]Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein:
Geometric deep learning on graphs and manifolds using mixture model CNNs. CoRR abs/1611.08402 (2016) - 2015
- [j38]Davide Boscaini, Davide Eynard, Drosos Kourounis, Michael M. Bronstein:
Shape-from-Operator: Recovering Shapes from Intrinsic Operators. Comput. Graph. Forum 34(2): 265-274 (2015) - [j37]Davide Boscaini, Jonathan Masci, Simone Melzi, Michael M. Bronstein, Umberto Castellani, Pierre Vandergheynst:
Learning class-specific descriptors for deformable shapes using localized spectral convolutional networks. Comput. Graph. Forum 34(5): 13-23 (2015) - [j36]Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein, Klaus Glashoff, Alexander M. Bronstein:
Multimodal Manifold Analysis by Simultaneous Diagonalization of Laplacians. IEEE Trans. Pattern Anal. Mach. Intell. 37(12): 2505-2517 (2015) - [c67]Artiom Kovnatsky, Michael M. Bronstein, Xavier Bresson, Pierre Vandergheynst:
Functional correspondence by matrix completion. CVPR 2015: 905-914 - [c66]Jan Svoboda, Michael M. Bronstein, Martin Drahanský:
Contactless biometric hand geometry recognition using a low-cost 3D camera. ICB 2015: 452-457 - [c65]Nauman Shahid, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst:
Robust Principal Component Analysis on Graphs. ICCV 2015: 2812-2820 - [c64]Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst:
Geodesic Convolutional Neural Networks on Riemannian Manifolds. ICCV Workshops 2015: 832-840 - [e8]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part I. Lecture Notes in Computer Science 8925, Springer 2015, ISBN 978-3-319-16177-8 [contents] - [e7]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II. Lecture Notes in Computer Science 8926, Springer 2015, ISBN 978-3-319-16180-8 [contents] - [e6]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part III. Lecture Notes in Computer Science 8927, Springer 2015, ISBN 978-3-319-16198-3 [contents] - [e5]Lourdes Agapito, Michael M. Bronstein, Carsten Rother:
Computer Vision - ECCV 2014 Workshops - Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part IV. Lecture Notes in Computer Science 8928, Springer 2015, ISBN 978-3-319-16219-5 [contents] - [e4]Matthias Teschner, Michael M. Bronstein:
36th Annual Conference of the European Association for Computer Graphics, Eurographics 2015 - Education Papers, Zurich, Switzerland, May 4-8, 2015. Eurographics Association 2015 [contents] - [r1]Alexander M. Bronstein, Michael M. Bronstein:
Manifold Intrinsic Similarity. Handbook of Mathematical Methods in Imaging 2015: 1859-1908 - [i26]Jonathan Masci, Davide Boscaini, Michael M. Bronstein, Pierre Vandergheynst:
ShapeNet: Convolutional Neural Networks on Non-Euclidean Manifolds. CoRR abs/1501.06297 (2015) - [i25]Nauman Shahid, Vassilis Kalofolias, Xavier Bresson, Michael M. Bronstein, Pierre Vandergheynst:
Robust Principal Component Analysis on Graphs. CoRR abs/1504.06151 (2015) - [i24]Artiom Kovnatsky, Klaus Glashoff, Michael M. Bronstein:
MADMM: a generic algorithm for non-smooth optimization on manifolds. CoRR abs/1505.07676 (2015) - [i23]Emanuele Rodolà, Luca Cosmo, Michael M. Bronstein, Andrea Torsello, Daniel Cremers:
Partial Functional Correspondence. CoRR abs/1506.05274 (2015) - 2014
- [j35]Davide Eynard, Artiom Kovnatsky, Michael M. Bronstein:
Laplacian colormaps: a framework for structure-preserving color transformations. Comput. Graph. Forum 33(2): 215-224 (2014) - [j34]Roee Litman, Alexander M. Bronstein, Michael M. Bronstein, Umberto Castellani:
Supervised learning of bag-of-features shape descriptors using sparse coding. Comput. Graph. Forum 33(5): 127-136 (2014) - [j33]Dan Raviv, Alexander M. Bronstein, Michael M. Bronstein, Dan Waisman, Nir A. Sochen, Ron Kimmel:
Equi-affine Invariant Geometry for Shape Analysis. J. Math. Imaging Vis. 50(1-2): 144-163 (2014) - [j32]Jonathan Masci, Michael M. Bronstein, Alexander M. Bronstein, Jürgen Schmidhuber:
Multimodal Similarity-Preserving Hashing. IEEE Trans. Pattern Anal. Mach. Intell. 36(4): 824-830 (2014) - [c63]Davide Boscaini, Ramunas Girdziusas, Michael M. Bronstein:
Coulomb Shapes: Using Electrostatic Forces for Deformation-invariant Shape Representation. 3DOR@Eurographics 2014: 9-15 - [c62]David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z. Cheng, Zhouhui Lian, Masaki Aono, Abdessamad Ben Hamza, Alexander M. Bronstein, Michael M. Bronstein, S. Bu, Umberto Castellani, S. Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, J. Han, Henry Johan, L. Lai, Bo Li, C. Li, Haisheng Li, Roee Litman, X. Liu, Z. Liu, Yijuan Lu, Atsushi Tatsuma, Jianbo Ye:
Shape Retrieval of Non-Rigid 3D Human Models. 3DOR@Eurographics 2014: 101-110 - [c61]Silvia Biasotti, Andrea Cerri, Alexander M. Bronstein, Michael M. Bronstein:
Quantifying 3D Shape Similarity Using Maps: Recent Trends, Applications and Perspectives. Eurographics (State of the Art Reports) 2014: 135-159 - [c60]Artiom Kovnatsky, Davide Eynard, Michael M. Bronstein:
Gamut mapping with image Laplacian commutators. ICIP 2014: 635-639 - [c59]