This repository is the official implementation of "DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models" accepted by the Main Technical Track of the 39th ...

Mumbai witnessed intense monsoon activity between 8 am and 1 pm on Sunday, with strong winds triggering widespread tree fall ...

General-purpose models struggle with messy, industry-specific data. A three-layer AI stack from Trunk Tools cut document ...

ANCHOR, a 3D human brainstem atlas, combines MRI and microscopy imaging to help researchers study neurodegenerative diseases ...

As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess ...

Abstract: Understanding the underlying graph structure of a nonlinear map over a particular domain is essential in evaluating its potential for real applications. In this paper, we investigate the ...

Context graphs, graph memory, and ontologies for AI are converging. What does this mean for enterprise AI in 2026?

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...

Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...

New benchmarks show semantic code graphs helping coding agents find change locations faster and complete updates more ...

While bears myopically focus on overvalued tech stocks, warning that a stock market bubble is beginning to burst, not only ...