Vadgama, Sharvaree

11 publications

ICLRW 2025 Clifford Group Equivariant Diffusion Models for 3D Molecular Generation Cong Liu, Sharvaree Vadgama, David Ruhe, Erik J Bekkers, Patrick Forré

ICML 2025 Controlled Generation with Equivariant Variational Flow Matching Floor Eijkelboom, Heiko Zimmermann, Sharvaree Vadgama, Erik J Bekkers, Max Welling, Christian A. Naesseth, Jan-Willem Van De Meent

ICLR 2025 Grounding Continuous Representations in Geometry: Equivariant Neural Fields David Wessels, David M Knigge, Riccardo Valperga, Samuele Papa, Sharvaree Vadgama, Efstratios Gavves, Erik J Bekkers

ICML 2025 On the Importance of Embedding Norms in Self-Supervised Learning Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, Erik J Bekkers

NeurIPS 2025 Probing Equivariance and Symmetry Breaking in Convolutional Networks Sharvaree Vadgama, Mohammad Mohaiminul Islam, Domas Buracas, Christian A Shewmake, Artem Moskalev, Erik J Bekkers

ICLR 2024 Fast, Expressive $\mathrm{SE}(n)$ Equivariant Networks Through Weight-Sharing in Position-Orientation Space Erik J Bekkers, Sharvaree Vadgama, Rob Hesselink, Putri A Van der Linden, David W. Romero

NeurIPS 2024 Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree Vadgama, Thijs P. Kuipers, Erik J. Bekkers

ICMLW 2024 Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors Putri A Van der Linden, Alejandro García Castellanos, Sharvaree Vadgama, Thijs P. Kuipers, Erik J Bekkers

ICMLW 2024 The Hidden Pitfalls of the Cosine Similarity Loss Andrew Draganov, Sharvaree Vadgama, Erik J Bekkers

NeurIPSW 2022 Kendall Shape-VAE : Learning Shapes in a Generative Framework Sharvaree Vadgama, Jakub Mikolaj Tomczak, Erik J Bekkers

NeurIPS 2019 Greedy Sampling for Approximate Clustering in the Presence of Outliers Aditya Bhaskara, Sharvaree Vadgama, Hong Xu