- 2024
- Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym:
Complete Neural Networks for Complete Euclidean Graphs. AAAI 2024: 12482-12490 - Christopher Morris, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Fabrizio Frasca, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Future Directions in Foundations of Graph Machine Learning. CoRR abs/2402.02287 (2024) - Snir Hordan, Tal Amir, Nadav Dym:
Weisfeiler Leman for Euclidean Equivariant Machine Learning. CoRR abs/2402.02484 (2024) - Nadav Dym, Hannah Lawrence, Jonathan W. Siegel:
Equivariant Frames and the Impossibility of Continuous Canonicalization. CoRR abs/2402.16077 (2024) - 2023
- Ingrid Daubechies, Ronald A. DeVore, Nadav Dym, Shira Faigenbaum-Golovin, Shahar Z. Kovalsky, Kung-Ching Lin, Josiah Park, Guergana Petrova, Barak Sober:
Neural Network Approximation of Refinable Functions. IEEE Trans. Inf. Theory 69(1): 482-495 (2023) - Tal Amir, Steven J. Gortler, Ilai Avni, Ravina Ravina, Nadav Dym:
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem. NeurIPS 2023 - Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym:
Complete Neural Networks for Euclidean Graphs. CoRR abs/2301.13821 (2023) - Tal Amir, Steven J. Gortler, Ilai Avni, Ravina Ravina, Nadav Dym:
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem. CoRR abs/2306.06529 (2023) - Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. CoRR abs/2310.13397 (2023) - Tamir Bendory, Nadav Dym, Dan Edidin, Arun Suresh:
Phase retrieval with semi-algebraic and ReLU neural network priors. CoRR abs/2311.08833 (2023) - 2022
- Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym:
A Simple and Universal Rotation Equivariant Point-Cloud Network. TAG-ML 2022: 107-115 - Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym:
A Simple and Universal Rotation Equivariant Point-cloud Network. CoRR abs/2203.01216 (2022) - Nadav Dym, Steven J. Gortler:
Low Dimensional Invariant Embeddings for Universal Geometric Learning. CoRR abs/2205.02956 (2022) - Tal Amir, Shahar Z. Kovalsky, Nadav Dym:
Symmetrized Robust Procrustes: Constant-Factor Approximation and Exact Recovery. CoRR abs/2207.08592 (2022) - 2021
- Nadav Dym, Haggai Maron:
On the Universality of Rotation Equivariant Point Cloud Networks. ICLR 2021 - Ingrid Daubechies, Ronald A. DeVore, Nadav Dym, Shira Faigenbaum-Golovin, Shahar Z. Kovalsky, Kung-Ching Lin, Josiah Park, Guergana Petrova, Barak Sober:
Neural Network Approximation of Refinable Functions. CoRR abs/2107.13191 (2021) - 2020
- Nadav Dym, Barak Sober, Ingrid Daubechies:
Expression of Fractals Through Neural Network Functions. IEEE J. Sel. Areas Inf. Theory 1(1): 57-66 (2020) - Cheng Cheng, Ingrid Daubechies, Nadav Dym, Jianfeng Lu:
Stable Phase Retrieval from Locally Stable and Conditionally Connected Measurements. CoRR abs/2006.11709 (2020) - Nadav Dym, Haggai Maron:
On the Universality of Rotation Equivariant Point Cloud Networks. CoRR abs/2010.02449 (2020) - 2019
- Yam Kushinsky, Haggai Maron, Nadav Dym, Yaron Lipman:
Sinkhorn Algorithm for Lifted Assignment Problems. SIAM J. Imaging Sci. 12(2): 716-735 (2019) - Nadav Dym, Shahar Z. Kovalsky:
Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration. ICCV 2019: 1628-1636 - Nadav Dym, Shahar Ziv Kovalsky:
Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration. CoRR abs/1904.02204 (2019) - Nadav Dym, Barak Sober, Ingrid Daubechies:
Expression of Fractals Through Neural Network Functions. CoRR abs/1905.11345 (2019) - 2018
- Nadav Dym:
Exact Recovery with Symmetries for the Doubly Stochastic Relaxation. SIAM J. Appl. Algebra Geom. 2(3): 462-488 (2018) - Roee Lazar, Nadav Dym, Yam Kushinsky, Zhiyang Huang, Tao Ju, Yaron Lipman:
Robust optimization for topological surface reconstruction. ACM Trans. Graph. 37(4): 46 (2018) - 2017
- Nadav Dym, Yaron Lipman:
Exact Recovery with Symmetries for Procrustes Matching. SIAM J. Optim. 27(3): 1513-1530 (2017) - Nadav Dym, Haggai Maron, Yaron Lipman:
DS++: a flexible, scalable and provably tight relaxation for matching problems. ACM Trans. Graph. 36(6): 184:1-184:14 (2017) - Haggai Maron, Meirav Galun, Noam Aigerman, Miri Trope, Nadav Dym, Ersin Yumer, Vladimir G. Kim, Yaron Lipman:
Convolutional neural networks on surfaces via seamless toric covers. ACM Trans. Graph. 36(4): 71:1-71:10 (2017) - Nadav Dym, Haggai Maron, Yaron Lipman:
DS++: A flexible, scalable and provably tight relaxation for matching problems. CoRR abs/1705.06148 (2017) - Nadav Dym, Yaron Lipman, Raz Slutsky:
A Linear Variational Principle for Riemann Mapping and Discrete Conformality. CoRR abs/1711.02221 (2017)