Nadav Dym

According to our database, Nadav Dym authored at least 31 papers between 2015 and 2024.

Collaborative distances:

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

2024

Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations.

Yonatan Sverdlov, Ido Springer, Nadav Dym

CoRR, 2024

On the Expressive Power of Sparse Geometric MPNNs.

Yonatan Sverdlov, Nadav Dym

CoRR, 2024

On the Hölder Stability of Multiset and Graph Neural Networks.

Yair Davidson, Nadav Dym

CoRR, 2024

Injective Sliced-Wasserstein embedding for weighted sets and point clouds.

Tal Amir, Nadav Dym

CoRR, 2024

A transversality theorem for semi-algebraic sets with application to signal recovery from the second moment and cryo-EM.

Tamir Bendory, Nadav Dym, Dan Edidin, Arun Suresh

CoRR, 2024

Future Directions in Foundations of Graph Machine Learning.

Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

CoRR, 2024

Equivariant Deep Weight Space Alignment.

Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Weisfeiler Leman for Euclidean Equivariant Machine Learning.

Snir Hordan, Tal Amir, Nadav Dym

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Equivariant Frames and the Impossibility of Continuous Canonicalization.

Nadav Dym, Hannah Lawrence, Jonathan W. Siegel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Future Directions in the Theory of Graph Machine Learning.

Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Complete Neural Networks for Complete Euclidean Graphs.

Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Neural Network Approximation of Refinable Functions.

Ingrid Daubechies, Ronald A. DeVore, Nadav Dym, Shira Faigenbaum-Golovin, Shahar Z. Kovalsky, Kung-Ching Lin, Josiah Park, Guergana Petrova, Barak Sober

IEEE Trans. Inf. Theory, 2023

Phase retrieval with semi-algebraic and ReLU neural network priors.

Tamir Bendory, Nadav Dym, Dan Edidin, Arun Suresh

CoRR, 2023

Complete Neural Networks for Euclidean Graphs.

Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym

CoRR, 2023

Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem.

Tal Amir, Steven J. Gortler, Ilai Avni, Ravina Ravina, Nadav Dym

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Symmetrized Robust Procrustes: Constant-Factor Approximation and Exact Recovery.

Tal Amir, Shahar Z. Kovalsky, Nadav Dym

CoRR, 2022

Low Dimensional Invariant Embeddings for Universal Geometric Learning.

Nadav Dym, Steven J. Gortler

CoRR, 2022

A Simple and Universal Rotation Equivariant Point-Cloud Network.

Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym

Proceedings of the Topological, 2022

2021

On the Universality of Rotation Equivariant Point Cloud Networks.

Nadav Dym, Haggai Maron

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Expression of Fractals Through Neural Network Functions.

Nadav Dym, Barak Sober, Ingrid Daubechies

IEEE J. Sel. Areas Inf. Theory, 2020

Stable Phase Retrieval from Locally Stable and Conditionally Connected Measurements.

Cheng Cheng, Ingrid Daubechies, Nadav Dym, Jianfeng Lu

CoRR, 2020

2019

Sinkhorn Algorithm for Lifted Assignment Problems.

Yam Kushinsky, Haggai Maron, Nadav Dym, Yaron Lipman

SIAM J. Imaging Sci., 2019

Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration.

Nadav Dym, Shahar Z. Kovalsky

Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018

Robust optimization for topological surface reconstruction.

Roee Lazar, Nadav Dym, Yam Kushinsky, Zhiyang Huang, Tao Ju, Yaron Lipman

ACM Trans. Graph., 2018

Exact Recovery with Symmetries for the Doubly Stochastic Relaxation.

Nadav Dym

SIAM J. Appl. Algebra Geom., 2018

2017

Convolutional neural networks on surfaces via seamless toric covers.

Haggai Maron, Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G. Kim, Yaron Lipman

ACM Trans. Graph., 2017

DS++: a flexible, scalable and provably tight relaxation for matching problems.

Nadav Dym, Haggai Maron, Yaron Lipman

ACM Trans. Graph., 2017

Exact Recovery with Symmetries for Procrustes Matching.

Nadav Dym, Yaron Lipman

SIAM J. Optim., 2017

A Linear Variational Principle for Riemann Mapping and Discrete Conformality.

Nadav Dym, Yaron Lipman, Raz Slutsky

CoRR, 2017

2016

Point registration via efficient convex relaxation.

Haggai Maron, Nadav Dym, Itay Kezurer, Shahar Z. Kovalsky, Yaron Lipman

ACM Trans. Graph., 2016

2015

Homotopic Morphing of Planar Curves.

Nadav Dym, Anna Shtengel, Yaron Lipman

Comput. Graph. Forum, 2015