Sharvaree Vadgama

According to our database, Sharvaree Vadgama authored at least 22 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Recursive Flow Matching.

Jiahe Huang, Sihan Xu, Sharvaree Vadgama, Rose Yu

CoRR, May, 2026

ToolMol: Evolutionary Agentic Framework for Multi-objective Drug Discovery.

Andrew Y. Zhou, Sharvaree Vadgama, Sumanth Varambally, Peter Eckmann, Michael K. Gilson, Rose Yu

CoRR, May, 2026

Think like a Scientist: Physics-guided LLM Agent for Equation Discovery.

Jianke Yang, Ohm Venkatachalam, Mohammad Kianezhad, Sharvaree Vadgama, Rose Yu

CoRR, February, 2026

2025

Longitudinal Flow Matching for Trajectory Modeling.

Mohammad Mohaiminul Islam, Thijs P. Kuipers, Sharvaree P. Vadgama, Coen de Vente, Afsana Khan, Clara I. Sánchez, Erik J. Bekkers

CoRR, October, 2025

Platonic Transformers: A Solid Choice For Equivariance.

Mohammad Mohaiminul Islam, Rishabh Anand, David R. Wessels, Friso de Kruiff, Thijs P. Kuipers, Rex Ying, Clara I. Sánchez, Sharvaree Vadgama, Georg Bökman, Erik J. Bekkers

CoRR, October, 2025

Clifford Group Equivariant Diffusion Models for 3D Molecular Generation.

Cong Liu, Sharvaree Vadgama, David Ruhe, Erik J. Bekkers, Patrick Forré

CoRR, April, 2025

On the Utility of Equivariance and Symmetry Breaking in Deep Learning Architectures on Point Clouds.

Sharvaree P. Vadgama, Mohammad Mohaiminul Islam, Domas Buracus, Christian Shewmake, Erik J. Bekkers

CoRR, January, 2025

Probing Equivariance and Symmetry Breaking in Convolutional Networks.

Sharvaree Vadgama, Mohammad Mohaiminul Islam, Domas Buracas, Christian Shewmake, Artem Moskalev, Erik J. Bekkers

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 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

Proceedings of the Forty-second International Conference on Machine Learning, 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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Grounding Continuous Representations in Geometry: Equivariant Neural Fields.

David R. Wessels, David M. Knigge, Riccardo Valperga, Samuele Papa, Sharvaree P. Vadgama, Efstratios Gavves, Erik J. Bekkers

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

DC3DO: Diffusion Classifier for 3D Objects.

Nursena Köprücü, Meher Shashwat Nigam, Shicheng Xu, Biruk Abere, Gabriele Dominici, Andrew Rodriguez, Sharvaree Vadgama, Berfin Inal, Alberto Tono

CoRR, 2024

The Hidden Pitfalls of the Cosine Similarity Loss.

Andrew Draganov, Sharvaree P. Vadgama, Erik J. Bekkers

CoRR, 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

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Preface to Geometry-grounded Representation Learning and Generative Modeling (GRaM) Workshop.

Sharvaree Vadgama, Erik J. Bekkers, Alison Pouplin, Sékou-Oumar Kaba, Robin Walters, Hannah Lawrence, Tegan Emerson, Henry Kvinge, Jakub M. Tomczak, Stefanie Jegelka

Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 2024

ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.

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 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

Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM) at ICML 2024, 2024

2023

Modeling Barrett's Esophagus Progression Using Geometric Variational Autoencoders.

Vivien van Veldhuizen, Sharvaree P. Vadgama, Onno J. de Boer, Sybren L. Meijer, Erik J. Bekkers

Proceedings of the Cancer Prevention Through Early Detection, 2023

Geometric Contrastive Learning.

Yeskendir Koishekenov, Sharvaree P. Vadgama, Riccardo Valperga, Erik J. Bekkers

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

Continuous Kendall Shape Variational Autoencoders.

Sharvaree P. Vadgama, Jakub M. Tomczak, Erik J. Bekkers

Proceedings of the Geometric Science of Information - 6th International Conference, 2023

2021

Interpretable ECG classification via a query-based latent space traversal (qLST).

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

CoRR, 2021

2019

Greedy Sampling for Approximate Clustering in the Presence of Outliers.

Aditya Bhaskara, Sharvaree Vadgama, Hong Xu

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019