Bronstein, Michael M.

Dynamic Graph CNN for Learning on Point Clouds

Wang, Y., Sun, Y., Liu, Z., Sarma, S. E., Bronstein, M. M., & Solomon, J. M. (2019) · ACM Transactions on Graphics

3D Shape Modeling and AnalysisAdvanced Neural Network Applications

Cited by 7,199

Geometric Deep Learning: Going beyond Euclidean data

Bronstein, M. M., Bruna, J., LeCun, Y., Szlam, A., & Vandergheynst, P. (2017) · IEEE Signal Processing Magazine

Advanced Graph Neural NetworksTopological and Geometric Data Analysis

Cited by 3,661

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs

Monti, F., Boscaini, D., Masci, J., Rodola, E., Svoboda, J., & Bronstein, M. M. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Graph Neural NetworksTopological and Geometric Data Analysis

Cited by 1,820

Geodesic Convolutional Neural Networks on Riemannian Manifolds

Masci, J., Boscaini, D., Bronstein, M. M., & Vandergheynst, P. (2015) · 2015 IEEE International Conference on Computer Vision Workshop (ICCVW)

3D Shape Modeling and AnalysisTopological and Geometric Data Analysis

Cited by 721

CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters

Levie, R., Monti, F., Bresson, X., & Bronstein, M. M. (2019) · IEEE Transactions on Signal Processing

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 685

LDAHash: Improved Matching with Smaller Descriptors

Strecha, C., Bronstein, A. M., Bronstein, M. M., & Fua, P. (2012) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Advanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

Cited by 605

Fake news detection on social media using geometric deep learning

Monti, F., Frasca, F., Eynard, D., Mannion, D., & Bronstein, M. M. (2019) · arXiv

Misinformation and Its ImpactsSpam and Phishing Detection

Cited by 392

Temporal Graph Networks for Deep Learning on Dynamic Graphs

Rossi, E., Chamberlain, B., Frasca, F., Eynard, D., Monti, F., & Bronstein, M. (2020) · arXiv

Advanced Graph Neural NetworksGraph Theory and Algorithms

Cited by 382

Utilizing graph machine learning within drug discovery and development

Gaudelet, T., Day, B., Jamasb, A. R., Soman, J., Regep, C., Liu, G., Hayter, J. B. R., Vickers, R., Roberts, C., Tang, J., et al. (2021) · Briefings in Bioinformatics

Computational Drug Discovery MethodsBioinformatics and Genomic Networks

Cited by 313

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

Bronstein, A. M., Bronstein, M. M., Kimmel, R., Mahmoudi, M., & Sapiro, G. (2010) · International Journal of Computer Vision

3D Shape Modeling and AnalysisTopological and Geometric Data Analysis

Cited by 267

Democratizing protein language model training, sharing and collaboration

Su, J., Li, Z., Tao, T., Han, C., He, Y., Dai, F., Yuan, Q., Gao, Y., Si, T., Zhang, X., et al. (2026) · Nature Biotechnology

Machine Learning in BioinformaticsProtein Structure and Dynamics

Cited by 35

Exploring “dark-matter” protein folds using deep learning

Harteveld, Z., Van Hall-Beauvais, A., Morozova, I., Southern, J., Goverde, C., Georgeon, S., Rosset, S., Defferrard, M., Loukas, A., Vandergheynst, P., et al. (2024) · Cell Systems

Protein Structure and DynamicsRNA and protein synthesis mechanisms

Cited by 13

Exploring “dark matter” protein folds using deep learning

Harteveld, Z., Van Hall-Beauvais, A., Morozova, I., Southern, J., Goverde, C., Georgeon, S., Rosset, S., Defferrard, M., Loukas, A., Vandergheynst, P., et al. (2023) · Cell Systems

Protein Structure and DynamicsRNA and protein synthesis mechanisms

Cited by 13