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Nadav Dym
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2020 – today
- 2024
- [c9]Snir Hordan, Tal Amir
, Steven J. Gortler, Nadav Dym:
Complete Neural Networks for Complete Euclidean Graphs. AAAI 2024: 12482-12490 - [c8]Christopher Morris, Fabrizio Frasca, Nadav Dym, Haggai Maron, Ismail Ilkan Ceylan, Ron Levie, Derek Lim, Michael M. Bronstein, Martin Grohe, Stefanie Jegelka:
Position: Future Directions in the Theory of Graph Machine Learning. ICML 2024 - [c7]Nadav Dym, Hannah Lawrence, Jonathan W. Siegel:
Equivariant Frames and the Impossibility of Continuous Canonicalization. ICML 2024 - [c6]Snir Hordan, Tal Amir, Nadav Dym:
Weisfeiler Leman for Euclidean Equivariant Machine Learning. ICML 2024 - [c5]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. ICML 2024 - [i23]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) - [i22]Snir Hordan, Tal Amir
Weisfeiler Leman for Euclidean Equivariant Machine Learning. CoRR abs/2402.02484 (2024) - [i21]Nadav Dym, Hannah Lawrence, Jonathan W. Siegel:
Equivariant Frames and the Impossibility of Continuous Canonicalization. CoRR abs/2402.16077 (2024) - [i20]Tamir Bendory, Nadav Dym, Dan Edidin, Arun Suresh:
A transversality theorem for semi-algebraic sets with application to signal recovery from the second moment and cryo-EM. CoRR abs/2405.04354 (2024) - [i19]Tal Amir
Injective Sliced-Wasserstein embedding for weighted sets and point clouds. CoRR abs/2405.16519 (2024) - [i18]Yair Davidson, Nadav Dym:
On the Hölder Stability of Multiset and Graph Neural Networks. CoRR abs/2406.06984 (2024) - [i17]Yonatan Sverdlov, Nadav Dym:
On the Expressive Power of Sparse Geometric MPNNs. CoRR abs/2407.02025 (2024) - [i16]Yonatan Sverdlov, Ido Springer, Nadav Dym:
Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations. CoRR abs/2410.06665 (2024) - [i15]Yonatan Sverdlov, Yair Davidson, Nadav Dym, Tal Amir:
FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network. CoRR abs/2410.09118 (2024) - 2023
- [j10]Ingrid Daubechies, Ronald A. DeVore, Nadav Dym, Shira Faigenbaum-Golovin, Shahar Z. Kovalsky, Kung-Ching Lin, Josiah Park
Neural Network Approximation of Refinable Functions. IEEE Trans. Inf. Theory 69(1): 482-495 (2023) - [c4]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 - [i14]Snir Hordan, Tal Amir, Steven J. Gortler, Nadav Dym:
Complete Neural Networks for Euclidean Graphs. CoRR abs/2301.13821 (2023) - [i13]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) - [i12]Aviv Navon, Aviv Shamsian, Ethan Fetaya, Gal Chechik, Nadav Dym, Haggai Maron:
Equivariant Deep Weight Space Alignment. CoRR abs/2310.13397 (2023) - [i11]Tamir Bendory, Nadav Dym, Dan Edidin, Arun Suresh:
Phase retrieval with semi-algebraic and ReLU neural network priors. CoRR abs/2311.08833 (2023) - 2022
- [c3]Ben Finkelshtein, Chaim Baskin, Haggai Maron, Nadav Dym:
A Simple and Universal Rotation Equivariant Point-Cloud Network. TAG-ML 2022: 107-115 - [i10]Ben Finkelshtein, Chaim Baskin
A Simple and Universal Rotation Equivariant Point-cloud Network. CoRR abs/2203.01216 (2022) - [i9]Nadav Dym, Steven J. Gortler:
Low Dimensional Invariant Embeddings for Universal Geometric Learning. CoRR abs/2205.02956 (2022) - [i8]Tal Amir
Symmetrized Robust Procrustes: Constant-Factor Approximation and Exact Recovery. CoRR abs/2207.08592 (2022) - 2021
- [c2]Nadav Dym, Haggai Maron:
On the Universality of Rotation Equivariant Point Cloud Networks. ICLR 2021 - [i7]Ingrid Daubechies, Ronald A. DeVore, Nadav Dym, Shira Faigenbaum-Golovin, Shahar Z. Kovalsky
Neural Network Approximation of Refinable Functions. CoRR abs/2107.13191 (2021) - 2020
- [j9]Nadav Dym, Barak Sober
Expression of Fractals Through Neural Network Functions. IEEE J. Sel. Areas Inf. Theory 1(1): 57-66 (2020) - [i6]Cheng Cheng, Ingrid Daubechies, Nadav Dym, Jianfeng Lu:
Stable Phase Retrieval from Locally Stable and Conditionally Connected Measurements. CoRR abs/2006.11709 (2020) - [i5]Nadav Dym, Haggai Maron:
On the Universality of Rotation Equivariant Point Cloud Networks. CoRR abs/2010.02449 (2020)
2010 – 2019
- 2019
- [j8]Yam Kushinsky, Haggai Maron, Nadav Dym, Yaron Lipman:
Sinkhorn Algorithm for Lifted Assignment Problems. SIAM J. Imaging Sci. 12(2): 716-735 (2019) - [c1]Nadav Dym, Shahar Z. Kovalsky:
Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration. ICCV 2019: 1628-1636 - [i4]Nadav Dym, Shahar Ziv Kovalsky:
Linearly Converging Quasi Branch and Bound Algorithms for Global Rigid Registration. CoRR abs/1904.02204 (2019) - [i3]Nadav Dym, Barak Sober, Ingrid Daubechies:
Expression of Fractals Through Neural Network Functions. CoRR abs/1905.11345 (2019) - 2018
- [j7]Nadav Dym:
Exact Recovery with Symmetries for the Doubly Stochastic Relaxation. SIAM J. Appl. Algebra Geom. 2(3): 462-488 (2018) - [j6]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
- [j5]Nadav Dym, Yaron Lipman:
Exact Recovery with Symmetries for Procrustes Matching. SIAM J. Optim. 27(3): 1513-1530 (2017) - [j4]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) - [j3]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) - [i2]Nadav Dym, Haggai Maron, Yaron Lipman:
DS++: A flexible, scalable and provably tight relaxation for matching problems. CoRR abs/1705.06148 (2017) - [i1]Nadav Dym, Yaron Lipman, Raz Slutsky:
A Linear Variational Principle for Riemann Mapping and Discrete Conformality. CoRR abs/1711.02221 (2017) - 2016
- [j2]Haggai Maron, Nadav Dym, Itay Kezurer, Shahar Z. Kovalsky, Yaron Lipman:
Point registration via efficient convex relaxation. ACM Trans. Graph. 35(4): 73:1-73:12 (2016) - 2015
- [j1]Nadav Dym, Anna Shtengel, Yaron Lipman:
Homotopic Morphing of Planar Curves. Comput. Graph. Forum 34(5): 239-251 (2015)
Coauthor Index
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last updated on 2024-11-25 23:40 CET by the dblp team
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