106 citations · 329 across the 20 of their papers we have counts for
22 papers
SCART: Simulation of Cyber Attacks for Real-Time
Eliron Rahimi, Kfir Girstein, Roman Malits +1
Real-Time systems are essential for promptly responding to external stimuli and completing tasks within predefined time constraints. Ensuring high reliability and robust security i…
AMED: Automatic Mixed-Precision Quantization for Edge Devices
Moshe Kimhi, Tal Rozen, Avi Mendelson +1
Quantized neural networks are well known for reducing the latency, power consumption, and model size without significant harm to the performance. This makes them highly appropriate…
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…
Graph Representation Learning via Aggregation Enhancement
Maxim Fishman, Chaim Baskin, Evgenii Zheltonozhskii +3
Graph neural networks (GNNs) have become a powerful tool for processing graph-structured data but still face challenges in effectively aggregating and propagating information betwe…
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels
Evgenii Zheltonozhskii, Chaim Baskin, Avi Mendelson +2
The success of learning with noisy labels (LNL) methods relies heavily on the success of a warm-up stage where standard supervised training is performed using the full (noisy) trai…