Phasio and Dyndrite introduce end-to-end HP MJF workflow - transforming customer demand directly into optimized builds.

Utilizing market research to inform decision-making begins with clearly identifying the objective: What specific goal am I ...

Abstract: Graph representation learning is a fundamental research theme and can be generalized to benefit multiple downstream tasks from the node and link levels to the higher graph level. In practice ...

Driven by our mission to make data and AI accessible, inclusive, and actionable, DataGlobal Hub curated a world-class agenda ...

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...

Abstract: Many studies have achieved excellent performance in analyzing graph-structured data. However, learning graph-level representations for graph classification is still a challenging task.

This is a PyTorch implementation of the GraphATA algorithm, which tries to address the multi-source domain adaptation problem without accessing the labelled source graph. Unlike previous multi-source ...

Horror buffs are discussing their limits when it comes to the extremes of the genre, whether that's because of body horror, torture, or animal abuse. "Animal abuse, hard no from me," said one user as ...