College of Computing - Georgia Tech

Transformer Explainer Shows How AI is More Math than Human

This sets unrealistic expectations for AI and leads to misuse. It also slows progress toward building new AI applications.
IEEE

Inconsistency-Aware Graph Convolutional Networks for Multi-View Classification

Abstract: Graph convolutional networks (GCNs) have attracted significant attention in the field of multi-view learning, as they effectively extract intricate information from diverse features.
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Tutorial for writing the equation of a cubic function from a graph

Description: 👉 Learn how to write the equation of a polynomial when given rational zeros. Recall that a polynomial is an expression of the form ax^n + bx^(n-1) + . . . + k, where a, b, and k are ...
EurekAlert!

PolyU develops novel AI graph neural network models to unravel interdisciplinary complexities in image recognition and neuroscience

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
IEEE

Graph Tensor Convolutional Network

Abstract: A dynamic graph (DG) is commonly encountered in many big data-related application scenarios, like cryptocurrency transaction analysis. A dynamic graph convolutional network (GCN) can ...
Scientific Research Publishing

Goodfellow, I. (2016) NIPS 2016 Tutorial: Generative Adversarial Networks. arXiv: 1701.00160.

ABSTRACT: This paper proposes a structured data prediction method based on Large Language Models with In-Context Learning (LLM-ICL). The method designs sample selection strategies to choose samples ...