In the realm of machine learning, training accurate and robust models is a constant pursuit. However, two common challenges that often hinder model performance are overfitting and underfitting.

Molecular machine learning (ML) underpins critical workflows in drug discovery, material science, and catalyst optimization ...

The paper elaborates on a technique for using knowledge graphs with machine learning; specifically, a branch of machine learning called reinforcement learning. This is something that holds great ...

Also: Google Next 2018: A deeper dive on AI and machine learning advances The paper explicitly draws upon work for more than a decade now on "graph neural networks." It also echoes some of the ...

The core product is a knowledge graph they claim has mapped “over ... they have released a short report about the state of the machine learning industry. The key slide I saw in the report ...

Year-to-date through September, Euclidean Fund I was up 9.8% net of fees and expenses in the context of the S&P 500 delivering a 10.6% total return, ...