4 citations · 7 across the 11 of their papers we have counts for
11 papers
The stability of generalized phase retrieval problem over compact groups
Tal Amir, Tamir Bendory, Nadav Dym +1
The generalized phase retrieval problem over compact groups aims to recover a set of matrices -- representing an unknown signal -- from their associated Gram matrices. This framewo…
Fourier Sliced-Wasserstein Embedding for Multisets and Measures
Tal Amir, Nadav Dym
We present the Fourier Sliced-Wasserstein (FSW) embedding - a novel method to embed multisets and measures over into Euclidean space. Our proposed embedding approxim…
FSW-GNN: A Bi-Lipschitz WL-Equivalent Graph Neural Network
Yonatan Sverdlov, Yair Davidson, Nadav Dym +1
Famously, the ability of Message Passing Neural Networks (MPNN) to distinguish between graphs is limited to graphs separable by the Weisfeiler-Lemann (WL) graph isomorphism test, a…
Fourier Sliced-Wasserstein Embedding for Multisets and Measures
Tal Amir, Nadav Dym
We present the Fourier Sliced-Wasserstein (FSW) embedding - a novel method to embed multisets and measures over R^d into Euclidean space. Our proposed embedding approximately prese…
Weisfeiler Leman for Euclidean Equivariant Machine Learning
Snir Hordan, Tal Amir, Nadav Dym
The -Weisfeiler-Leman (-WL) graph isomorphism test hierarchy is a common method for assessing the expressive power of graph neural networks (GNNs). Recently, GNNs whose expre…
Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem
Tal Amir, Steven J. Gortler, Ilai Avni +2
Injective multiset functions have a key role in the theoretical study of machine learning on multisets and graphs. Yet, there remains a gap between the provably injective multiset…
Complete Neural Networks for Complete Euclidean Graphs
Snir Hordan, Tal Amir, Steven J. Gortler +1
Neural networks for point clouds, which respect their natural invariance to permutation and rigid motion, have enjoyed recent success in modeling geometric phenomena, from molecula…
Symmetrized Robust Procrustes: Constant-Factor Approximation and Exact Recovery
Tal Amir, Shahar Kovalsky, Nadav Dym
The classical problem is to find a rigid motion (orthogonal transformation and translation) that best aligns two given point-sets in the least-squares sense.…
The Trimmed Lasso: Sparse Recovery Guarantees and Practical Optimization by the Generalized Soft-Min Penalty
Tal Amir, Ronen Basri, Boaz Nadler
We present a new approach to solve the sparse approximation or best subset selection problem, namely find a -sparse vector that minimizes the r…
A New Rank Constraint on Multi-view Fundamental Matrices, and its Application to Camera Location Recovery
Soumyadip Sengupta, Tal Amir, Meirav Galun +4
Accurate estimation of camera matrices is an important step in structure from motion algorithms. In this paper we introduce a novel rank constraint on collections of fundamental ma…
Wide baseline stereo matching with convex bounded-distortion constraints
Meirav Galun, Tal Amir, Tal Hassner +2
Finding correspondences in wide baseline setups is a challenging problem. Existing approaches have focused largely on developing better feature descriptors for correspondence and o…