Homotopic Morphing of Planar Curves. - Nadav Dym; Anna Shtengel; Yaron Lipman (Comput. Graph. Forum, 2015)

Point registration via efficient convex relaxation. - Haggai Maron; Nadav Dym; Itay Kezurer; Shahar Z. Kovalsky; Yaron Lipman (ACM Trans. Graph., 2016)

A Linear Variational Principle for Riemann Mapping and Discrete Conformality. - Nadav Dym; Yaron Lipman; Raz Slutsky (CoRR, 2017)

Exact Recovery with Symmetries for Procrustes Matching. - Nadav Dym; Yaron Lipman (SIAM J. Optim., 2017)

DS++: a flexible, scalable and provably tight relaxation for matching problems. - Nadav Dym; Haggai Maron; Yaron Lipman (ACM Trans. Graph., 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)

Exact Recovery with Symmetries for the Doubly Stochastic Relaxation. - Nadav Dym (SIAM J. Appl. Algebra Geom., 2018)

Robust optimization for topological surface reconstruction. - Roee Lazar; Nadav Dym; Yam Kushinsky; Zhiyang Huang; Tao Ju; Yaron Lipman (ACM Trans. Graph., 2018)

Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration. - Nadav Dym; Shahar Z. Kovalsky (ICCV, 2019)

Sinkhorn Algorithm for Lifted Assignment Problems. - Yam Kushinsky; Haggai Maron; Nadav Dym; Yaron Lipman (SIAM J. Imaging Sci., 2019)

Stable Phase Retrieval from Locally Stable and Conditionally Connected Measurements. - Cheng Cheng; Ingrid Daubechies; Nadav Dym; Jianfeng Lu 001 (CoRR, 2020)

Expression of Fractals Through Neural Network Functions. - Nadav Dym; Barak Sober; Ingrid Daubechies (IEEE J. Sel. Areas Inf. Theory, 2020)

On the Universality of Rotation Equivariant Point Cloud Networks. - Nadav Dym; Haggai Maron (ICLR, 2021)

A Simple and Universal Rotation Equivariant Point-Cloud Network. - Ben Finkelshtein; Chaim Baskin; Haggai Maron; Nadav Dym (TAG-ML, 2022)

Symmetrized Robust Procrustes: Constant-Factor Approximation and Exact Recovery. - Tal Amir; Shahar Z. Kovalsky; Nadav Dym (CoRR, 2022)

Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem. - Tal Amir; Steven J. Gortler; Ilai Avni; Ravina Ravina; Nadav Dym (NeurIPS, 2023)

Complete Neural Networks for Euclidean Graphs. - Snir Hordan; Tal Amir; Steven J. Gortler; Nadav Dym (CoRR, 2023)

Phase retrieval with semi-algebraic and ReLU neural network priors. - Tamir Bendory; Nadav Dym; Dan Edidin; Arun Suresh (CoRR, 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)

Complete Neural Networks for Complete Euclidean Graphs. - Snir Hordan; Tal Amir; Steven J. Gortler; Nadav Dym (AAAI, 2024)

Position: Future Directions in the Theory of Graph Machine Learning. - Christopher Morris 001; Fabrizio Frasca; Nadav Dym; Haggai Maron; Ismail Ilkan Ceylan; Ron Levie; Derek Lim; Michael M. Bronstein; Martin Grohe; Stefanie Jegelka (ICML, 2024)

Equivariant Frames and the Impossibility of Continuous Canonicalization. - Nadav Dym; Hannah Lawrence; Jonathan W. Siegel (ICML, 2024)

Weisfeiler Leman for Euclidean Equivariant Machine Learning. - Snir Hordan; Tal Amir; Nadav Dym (ICML, 2024)

Equivariant Deep Weight Space Alignment. - Aviv Navon; Aviv Shamsian; Ethan Fetaya; Gal Chechik; Nadav Dym; Haggai Maron (ICML, 2024)

Future Directions in Foundations of Graph Machine Learning. - Christopher Morris 001; Nadav Dym; Haggai Maron; Ismail Ilkan Ceylan; Fabrizio Frasca; Ron Levie; Derek Lim; Michael M. Bronstein; Martin Grohe; Stefanie Jegelka (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)

Injective Sliced-Wasserstein embedding for weighted sets and point clouds. - Tal Amir; Nadav Dym (CoRR, 2024)

FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network. - Yonatan Sverdlov; Yair Davidson; Nadav Dym; Tal Amir (CoRR, 2024)

Fourier Sliced-Wasserstein Embedding for Multisets and Measures. - Tal Amir; Nadav Dym (ICLR, 2025)

On the Hölder Stability of Multiset and Graph Neural Networks. - Yair Davidson; Nadav Dym (ICLR, 2025)

On the Expressive Power of Sparse Geometric MPNNs. - Yonatan Sverdlov; Nadav Dym (ICLR, 2025)

Revisiting Multi-Permutation Equivariance through the Lens of irreducible Representations. - Yonatan Sverdlov; Ido Springer; Nadav Dym (ICLR, 2025)

Bi-Lipschitz Ansatz for Anti-Symmetric Functions. - Nadav Dym; Jianfeng Lu; Matan Mizrachi (CoRR, 2025)

Low-Dimensional Invariant Embeddings for Universal Geometric Learning. - Nadav Dym; Steven J. Gortler (Found. Comput. Math., 2025)

The stability of generalized phase retrieval problem over compact groups. - Tal Amir; Tamir Bendory; Nadav Dym; Dan Edidin (CoRR, 2025)

On the (Non) Injectivity of Piecewise Linear Janossy Pooling. - Ilai Reshef; Nadav Dym (CoRR, 2025)

Spectral Graph Neural Networks are Incomplete on Graphs with a Simple Spectrum. - Snir Hordan; Maya Bechler-Speicher; Gur Lifshitz; Nadav Dym (CoRR, 2025)