Vandergheynst, Pierre

The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains

Shuman, D. I., Narang, S. K., Frossard, P., Ortega, A., & Vandergheynst, P. (2013) · IEEE Signal Processing Magazine

Advanced Graph Neural NetworksMathematical Analysis and Transform Methods

Cited by 4,421

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

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

Vertex-frequency analysis on graphs

Shuman, D. I., Ricaud, B., & Vandergheynst, P. (2016) · Applied and Computational Harmonic Analysis

Mathematical Analysis and Transform MethodsAdvanced Graph Neural Networks

Cited by 349

DTI mapping of human brain connectivity: Statistical fibre tracking and virtual dissection

Hagmann, P., Thiran, J.-P., Jonasson, L., Vandergheynst, P., Clarke, S., Maeder, P., & Meuli, R. (2003) · NeuroImage

Advanced Neuroimaging Techniques and ApplicationsFunctional Brain Connectivity Studies

Cited by 326

FMA: A Dataset for Music Analysis

Defferrard, M., Benzi, K., Vandergheynst, P., & Bresson, X. (2016) · arXiv

Music and Audio ProcessingMusic Technology and Sound Studies

Cited by 237

Global and local uncertainty principles for signals on graphs

Perraudin, N., Ricaud, B., Shuman, D. I., & Vandergheynst, P. (2018) · APSIPA Transactions on Signal and Information Processing

Mathematical Analysis and Transform MethodsSparse and Compressive Sensing Techniques

Cited by 58

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

Conditional deep learning model reveals translation elongation determinants during amino acid deprivation

Nallapareddy, M. V., Craighero, F., Worpenberg, L., Naef, F., Gobet, C., & Vandergheynst, P. (2025) · Communications Biology

RNA and protein synthesis mechanismsGenomics and Phylogenetic Studies

Cited by 1

Conditional Deep Learning Model Reveals Translation Elongation Determinants during Amino Acid Deprivation

Nallapareddy, M. V., Craighero, F., Worpenberg, L., Naef, F., Gobet, C., & Vandergheynst, P. (2025) · Communications Biology

RNA and protein synthesis mechanismsGenomics and Phylogenetic Studies

Cited by 1