| 2025 | ICLR | Fourier Sliced-Wasserstein Embedding for Multisets and Measures. | Tal Amir, Nadav Dym |
| 2025 | ICLR | On the Hlder Stability of Multiset and Graph Neural Networks. | Yair Davidson, Nadav Dym |
| 2025 | ICLR | On the Expressive Power of Sparse Geometric MPNNs. | Yonatan Sverdlov, Nadav Dym |
| 2025 | ICLR | Revisiting Multi-Permutation Equivariance through the Lens of irreducible Representations. | Yonatan Sverdlov, Ido Springer, Nadav Dym |
| 2024 | AAAI | Complete Neural Networks for Complete Euclidean Graphs. | Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym |
| 2024 | ICML | 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 |
| 2024 | ICML | Equivariant Frames and the Impossibility of Continuous Canonicalization. | Nadav Dym, Hannah Lawrence, Jonathan W. Siegel |
| 2024 | ICML | Weisfeiler Leman for Euclidean Equivariant Machine Learning. | Snir Hordan, Tal Amir, Nadav Dym |
| 2024 | ICML | Equivariant Deep Weight Space Alignment. | Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron |
| 2021 | ICLR | On the Universality of Rotation Equivariant Point Cloud Networks. | Nadav Dym, Haggai Maron |
| 2019 | ICCV | Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration. | Nadav Dym, Shahar Z. Kovalsky |