Greedy sampling for approximate clustering in the presence of outliers A Bhaskara, S Vadgama, H Xu
Advances in Neural Information Processing Systems 32, 2019
33 2019 Fast, Expressive EJ Bekkers, S Vadgama, R Hesselink, PA Van der Linden, DW Romero
The Twelfth International Conference on Learning Representations, 2024
17 * 2024 Kendall shape-VAE: Learning shapes in a generative framework S Vadgama, JM Tomczak, EJ Bekkers
NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022
11 2022 Almost-global exponential tracking of a variable pitch quadrotor on SE (3) A Simha, S Vadgama, S Raha
IFAC-PapersOnLine 50 (1), 10268-10273, 2017
7 2017 A geometric approach to rotor failure tolerant trajectory tracking control design for a quadrotor A Simha, S Vadgama, S Raha
arXiv preprint arXiv:1704.00327, 2017
6 2017 Grounding Continuous Representations in Geometry: Equivariant Neural Fields DR Wessels, DM Knigge, S Papa, R Valperga, S Vadgama, E Gavves, ...
arXiv preprint arXiv:2406.05753, 2024
3 2024 Continuous Kendall Shape Variational Autoencoders S Vadgama, JM Tomczak, E Bekkers
International Conference on Geometric Science of Information, 73-81, 2023
3 2023 Geometric Contrastive Learning Y Koishekenov, S Vadgama, R Valperga, EJ Bekkers
Proceedings of the IEEE/CVF International Conference on Computer Vision, 206-215, 2023
3 2023 ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain G Bernárdez, L Telyatnikov, M Montagna, F Baccini, M Papillon, ...
arXiv preprint arXiv:2409.05211, 2024
1 2024 Interpretable ECG classification via a query-based latent space traversal (qLST) MB Vessies, SP Vadgama, RR van de Leur, PA Doevendans, RJ Hassink, ...
arXiv preprint arXiv:2111.07386, 2021
1 2021 On the Importance of Embedding Norms in Self-Supervised Learning A Draganov, S Vadgama, S Damrich, JN Böhm, L Maes, D Kobak, ...
arXiv preprint arXiv:2502.09252, 2025
2025 On the Utility of Equivariance and Symmetry Breaking in Deep Learning Architectures on Point Clouds S Vadgama, MM Islam, D Buracus, C Shewmake, E Bekkers
arXiv preprint arXiv:2501.01999, 2025
2025 Learning symmetries via weight-sharing with doubly stochastic tensors PA Van der Linden, A García-Castellanos, S Vadgama, TP Kuipers, ...
arXiv preprint arXiv:2412.04594, 2024
2024 Preface to Geometry-grounded Representation Learning and Generative Modeling (GRaM) Workshop S Vadgama, E Bekkers, A Pouplin, SO Kaba, R Walters, H Lawrence, ...
Geometry-grounded Representation Learning and Generative Modeling Workshop …, 2024
2024 DC3DO: Diffusion Classifier for 3D Objects N Koprucu, MS Nigam, S Xu, B Abere, G Dominici, A Rodriguez, ...
arXiv preprint arXiv:2408.06693, 2024
2024 The hidden pitfalls of the cosine similarity loss A Draganov, S Vadgama, EJ Bekkers
arXiv preprint arXiv:2406.16468, 2024
2024 Modeling Barrett’s Esophagus Progression Using Geometric Variational Autoencoders V van Veldhuizen, S Vadgama, O de Boer, S Meijer, EJ Bekkers
MICCAI Workshop on Cancer Prevention through Early Detection, 132-142, 2023
2023 Black rings S Vadgama
Indian Institute of Science Education and Research (IISER) Pune, 2016
2016 
Erik J BekkersUniversity of AmsterdamZweryfikowany adres z uva.nl