Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured ...

Forecasting is a fundamentally new capability that is missing from the current purview of generative AI. Here's how Kumo is changing that.

In recent years, with the public availability of AI tools, more people have become aware of how closely the inner workings of ...

New research reveals a surprising geometric link between human and machine learning. A mathematical property called convexity ...

New research reveals a surprising geometric link between human and machine learning. A mathematical property called convexity may help explain how ...

Contrastive learning has been widely used in graph representation learning, which extracts node or graph representations by contrasting positive and negative node pairs. It requires node ...

For enterprise adoption to achieve its full potential, particularly in mission and safety-critical applications, several ...

As Large Language Models (LLMs) are widely used for tasks like document summarization, legal analysis, and medical history ...

AI-driven math hints do more than nudge students toward a correct answer--they help students develop confidence and ...

Autonomous Systems Lead the Next Era of Digital Productivity and Cognitive Automation. ROCKVILLE, MD, UNITED STATES, June 20, 2025 /EINPresswire.com/ -- According to Fact.MR, a market research and ...

In today’s data-driven world, graphs are everywhere—from COVID-19 curves and economic forecasts to climate models and ...