2 citations · 4 across the 2 of their papers we have counts for
3 papers
quant-ph2026
Quantum Graph Convolutional Networks: Implementation and Trainability Analysis
Paul San Sebastian Sein, Theodor Iosif, Tilen G. Limbäck-Stokin +2
Graph Neural Networks (GNNs) achieve state-of-the-art performance on graph-structured data, but training and inference on large graphs are often bottlenecked by memory constraints…
quant-ph2024★ 2 cited
Graph Neural Networks on Quantum Computers
Yidong Liao, Xiao-Ming Zhang, Chris Ferrie
Graph Neural Networks (GNNs) are powerful machine learning models that excel at analyzing structured data represented as graphs, demonstrating remarkable performance in application…
quant-ph2024★ 2 cited
GPT on a Quantum Computer
Yidong Liao, Chris Ferrie
Large Language Models (LLMs) such as ChatGPT have transformed how we interact with and understand the capabilities of Artificial Intelligence (AI). However, the intersection of LLM…