Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks. - Radu A. Cosma; Lukas Knobel; Putri A. van der Linden; David M. Knigge; Erik J. Bekkers (ICCV (Workshops), 2023)

Learned Gridification for Efficient Point Cloud Processing. - Putri A. van der Linden; David W. Romero; Erik J. Bekkers (TAG-ML, 2023)

Conformal time series decomposition with component-wise exchangeability. - Derck W. E. Prinzhorn; Thijmen Nijdam; Putri A. van der Linden; Alexander Timans (COPA, 2024)

Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. - Erik J. Bekkers; Sharvaree P. Vadgama; Rob Hesselink; Putri A. van der Linden; David W. Romero (ICLR, 2024)

Learning symmetries via weight-sharing with doubly stochastic tensors. - Putri A. van der Linden; Alejandro García-Castellanos; Sharvaree P. Vadgama; Thijs P. Kuipers; Erik J. Bekkers (NeurIPS, 2024)

CP2: Leveraging Geometry for Conformal Prediction via Canonicalization. - Putri A. van der Linden; Alexander Timans; Erik J. Bekkers (UAI, 2025)

On Equivariant Model Selection through the Lens of Uncertainty. - Putri A. van der Linden; Alexander Timans; Dharmesh Tailor; Erik J. Bekkers (CoRR, 2025)