IPA-GNN

2000년 도입 · 논문 1편에서 사용

Instruction Pointer Attention Graph Neural Network, or IPA-GNN, is a learning-interpreter neural network (LNN) based on GNNs for learning to execute programmes. It achieves improved systematic generalization on the task of learning to execute programs using control flow graphs. The model arises by considering RNNs operating on program traces with branch decisions as latent variables. The IPA-GNN can be seen either as a continuous relaxation of the RNN model or as a GNN variant more tailored to execution.

출처: Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks

소개 논문: Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks