iclr神经网络-阿里云

ICLR 2024 Spotlight：训练一个图神经网络即可解决图领域所有分类问题！

在人工智能的发展浪潮中，模型的通用性和适应性一直是研究者们追求的目标。尤其是在处理图结构数据方面，如何设计一个能够应对各种分类任务的统一模型，成为了一个重要的研究方向。近年来，大型语言模型（LLMs）在自然语言处理领域取得了显著的成就，但相比之下，图结构数据的统一模型开发却相对滞后。这一现象的背后，...

ICLR 2023 Oral | 漂移感知动态神经网络加持，时间域泛化新框架远超领域泛化&适应方法

在领域泛化 (Domain Generalization, DG) 任务中，当领域的分布随环境连续变化时，如何准确地捕捉该变化以及其对模型的影响是非常重要但也极富挑战的问题。为此，来自 Emory 大学的赵亮教授团队，提出了一种基于贝叶斯理论的时间域泛化框架 DRAIN，利用递归网络学习时间维度领域...

神经网络概览及算法详解

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iclr 2020 | Geom-GCN：几何图神经网络

今天给大家介绍吉林大学计算机科学与技术学院杨博老师团队在ICLR2020的一篇论文，该研究针对MPNN现存的一些问题提出了一种新的图神经网络的几何聚合方式，其核心思想是：图上的聚合可以受益于图的连续空间，实验结果表明该研究具有显著效果。1背景消息传递神经网络（MPNN），例如GNN，C...

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