AlphaGalileo

Simplified Multi-view Graph Neural Network for Multilingual Knowledge Graph Completion

SM-GNN prunes multi-view GNNs to pure propagation, cutting training time while outperforming prior MKGC accuracies on two ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
IEEE

Tensor-based Graph Learning with Consistency and Specificity for Multi-view Clustering

Abstract: In the context of multi-view clustering, graph learning is recognized as a crucial technique, which generally involves constructing an adaptive neighbor graph based on probabilistic ...
Frontiers

A multi-view multimodal deep learning framework for Alzheimer's disease diagnosis

Introduction: Early diagnosis of Alzheimer's disease (AD) remains challenging due to the high similarity among AD, mild cognitive impairment (MCI), and cognitively normal (CN) individuals, as well as ...
The New York Times

What A.I. Really Means for Learning

A.I. is fueling a “poverty of imagination.” Here’s how we can fix it. By Meher AhmadJessica Grose and Tressie McMillan Cottom Produced by Vishakha Darbha Artificial intelligence is already showing up ...
Frontiers

Leveraging unified multi-view hypergraph learning for neurodevelopmental disorders diagnosis

1 School of Software, Tsinghua University, Beijing, China 2 Shenzhen Clinical Research Center for Mental Disorders, Shenzhen Kangning Hospital and Shenzhen Mental Health Center, Shenzhen, China ...
IEEE

Bidirectional Probabilistic Multi-Graph Learning and Decomposition for Multi-View Clustering

Abstract: Graph-based multi-view clustering has attracted remarkable attention due to its impressive performance. However, the typical framework consisting of graph learning and indicator generation ...