I am a computational biologist interested in interpretable machine learning for genomics and health care. Interpretable ...

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

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

Machine learning methods enable computers to learn without being explicitly programmed and have multiple applications, for example, in the improvement of data mining algorithms.

Jakob Rissmann, Principal Product Owner of Data Services at FlixBus, says Snowflake serves as the company's centralized data platform, where employees collect information and run queries across the ...

Medical image analysis has rapidly advanced in the identification and characterization of lesions. Despite advancements, deep ...

Maternal mortality is a major public health concern worldwide. It is the number of preventable deaths that occur each year due to pregnancy and childbirth. The research investigates how machine ...

The reinforcement learning paradigm is a widely used approach to solving sequential problems. In this paper, we utilized reinforcement learning with curriculum learning to train the agent to play ...

Conference marking 100 years of quantum mechanics starts in Hamburg Turns out that Zeilinger (as Albert Einstein once was) is a keen sailor in his spare time and he and his wife had come to Helgoland ...

A correlogram or correlation matrix allows to analyse the relationship between each pair of numeric variables of a dataset. The relationship between each pair of variable is visualised through a ...