12 citations · 48 across the 17 of their papers we have counts for
11 papers · 1 filter
TemporalGraphLLM: Temporal Graph Neural Networks with Large Language Models for Dynamic Text-Attributed Graphs
Moran Beladev, Or Eitan, Gilad Katz +1
Dynamic text-attributed graphs (DTAGs), where nodes, edges, and textual attributes evolve over time, are crucial in applications such as social networks, citation graphs, and knowl…
Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections
Gil Lifshits, Igal Bilik, Gilad Katz
Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with com…
Anomaly Detection for Aggregated Data Using Multi-Graph Autoencoder
Tomer Meirman, Roni Stern, Gilad Katz
In data systems, activities or events are continuously collected in the field to trace their proper executions. Logging, which means recording sequences of events, can be used for…
Hierarchical Deep Reinforcement Learning Approach for Multi-Objective Scheduling With Varying Queue Sizes
Yoni Birman, Ziv Ido, Gilad Katz +1
Multi-objective task scheduling (MOTS) is the task scheduling while optimizing multiple and possibly contradicting constraints. A challenging extension of this problem occurs when…
PIVEN: A Deep Neural Network for Prediction Intervals with Specific Value Prediction
Eli Simhayev, Gilad Katz, Lior Rokach
Improving the robustness of neural nets in regression tasks is key to their application in multiple domains. Deep learning-based approaches aim to achieve this goal either by impro…
Automatic Machine Learning Derived from Scholarly Big Data
Asnat Greenstein-Messica, Roman Vainshtein, Gilad Katz +2
One of the challenging aspects of applying machine learning is the need to identify the algorithms that will perform best for a given dataset. This process can be difficult, time c…