10 citations · 12 across the 13 of their papers we have counts for
13 papers · 1 filter
Revisiting Node Affinity Prediction in Temporal Graphs
Or Feldman, Krishna Sri Ipsit Mantri, Moshe Eliasof +1
Node affinity prediction is a common task that is widely used in temporal graph learning with applications in social and financial networks, recommender systems, and more. Recent w…
Adversarial Attacks in Weight-Space Classifiers
Tamir Shor, Ethan Fetaya, Chaim Baskin +1
Implicit Neural Representations (INRs) have been recently garnering increasing interest in various research fields, mainly due to their ability to represent large, complex data in…
Hysteresis Activation Function for Efficient Inference
Moshe Kimhi, Idan Kashani, Avi Mendelson +1
The widely used ReLU is favored for its hardware efficiency, {as the implementation at inference is a one bit sign case,} yet suffers from issues such as the ``dying ReLU'' problem…
Sequential Signal Mixing Aggregation for Message Passing Graph Neural Networks
Mitchell Keren Taraday, Almog David, Chaim Baskin
Message Passing Graph Neural Networks (MPGNNs) have emerged as the preferred method for modeling complex interactions across diverse graph entities. While the theory of such models…
Bimodal Distributed Binarized Neural Networks
Tal Rozen, Moshe Kimhi, Brian Chmiel +2
Binary Neural Networks (BNNs) are an extremely promising method to reduce deep neural networks' complexity and power consumption massively. Binarization techniques, however, suffer…
Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-Colorings
Or Feldman, Amit Boyarski, Shai Feldman +3
Graph isomorphism testing is usually approached via the comparison of graph invariants. Two popular alternatives that offer a good trade-off between expressive power and computatio…