A framework for analyzing single-cell genomics data, in which geometrical properties are harnessed to obtain insights on cellular diversity, including precise clustering, clear visualizations, and ...

Katherine Chui, a graphics reporter, analyzed two centuries of census and congressional data. Emily Cochrane is based in Nashville and covers the American South. April 30, 2026 The central tenet of ...

Abstract: Generative graph models have recently emerged as a powerful paradigm in self-supervised learning (SSL) for graph representation tasks, demonstrating remarkable potential in capturing complex ...

Veloclade is a research prototype of a neuro-symbolic knowledge graph system. It uses clade-inspired hierarchy + embedding clustering (sentence-transformers) to control ontology growth and mitigate ...

Abstract: In the field of graph self-supervised learning (GSSL), graph autoencoders and graph contrastive learning are two mainstream methods. Graph autoencoders aim to learn representations by ...

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Best laptop cooling pads Best flip ...

Machine learning has expanded beyond traditional Euclidean spaces in recent years, exploring representations in more complex geometric structures. Non-Euclidean representation learning is a growing ...

The challenge of managing and recalling facts from complex, evolving conversations is a key problem for many AI-driven applications. As information grows and changes over time, maintaining accurate ...

The PyGSP2 is a Python package to ease Signal Processing on Graphs. The documentation is available on Read the Docs and development takes place on GitHub. A (mostly unmaintained) Matlab version exists ...