Sharvaree P. Vadgama

15 papers A* 3Journal 9Unranked 3
YearRankTypeTitle / Venue / Authors
2025 A* conf
Grounding Continuous Representations in Geometry: Equivariant Neural Fields.
ICLR
David R. Wessels, David M. Knigge, Riccardo Valperga, Samuele Papa, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers
2025 J jnl
Longitudinal Flow Matching for Trajectory Modeling.
CoRR
Mohammad Mohaiminul Islam, Thijs P. Kuipers, Sharvaree P. Vadgama, Coen de Vente, Afsana Khan, Clara I. Sánchez, Erik J. Bekkers
2025 J jnl
On the Importance of Embedding Norms in Self-Supervised Learning.
CoRR
Andrew Draganov, Sharvaree P. Vadgama, Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, Erik J. Bekkers
2025 J jnl
On the Utility of Equivariance and Symmetry Breaking in Deep Learning Architectures on Point Clouds.
CoRR
Sharvaree P. Vadgama, Mohammad Mohaiminul Islam, Domas Buracus, Christian Shewmake, Erik J. Bekkers
2024 A* conf
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space.
ICLR
Erik J. Bekkers, Sharvaree P. Vadgama, Rob Hesselink, Putri A. van der Linden, David W. Romero
2024 J jnl
Grounding Continuous Representations in Geometry: Equivariant Neural Fields.
CoRR
David R. Wessels, David M. Knigge, Samuele Papa, Riccardo Valperga, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers
2024 J jnl
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.
CoRR
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024 J jnl
Learning Symmetries via Weight-Sharing with Doubly Stochastic Tensors.
CoRR
Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree P. Vadgama, Thijs P. Kuipers, Erik J. Bekkers
2024 A* conf
Learning symmetries via weight-sharing with doubly stochastic tensors.
NeurIPS
Putri A. van der Linden, Alejandro García-Castellanos, Sharvaree P. Vadgama, Thijs P. Kuipers, Erik J. Bekkers
2024 J jnl
The Hidden Pitfalls of the Cosine Similarity Loss.
CoRR
Andrew Draganov, Sharvaree P. Vadgama, Erik J. Bekkers
2023 — conf
Continuous Kendall Shape Variational Autoencoders.
GSI (1)
Sharvaree P. Vadgama, Jakub M. Tomczak, Erik J. Bekkers
2023 J jnl
Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space.
CoRR
Erik J. Bekkers, Sharvaree P. Vadgama, Rob D. Hesselink, Putri A. van der Linden, David W. Romero
2023 — conf
Geometric Contrastive Learning.
ICCV (Workshops)
Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers
2023 — conf
Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders.
CaPTion@MICCAI
Vivien van Veldhuizen, Sharvaree P. Vadgama, Onno J. de Boer, Sybren L. Meijer, Erik J. Bekkers
2021 J jnl
Interpretable ECG classification via a query-based latent space traversal (qLST).
CoRR
Melle B. Vessies, Sharvaree P. Vadgama, Rutger R. van de Leur, Pieter A. F. M. Doevendans, Rutger J. Hassink, Erik J. Bekkers, René van Es