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

The fact that LLMs are used to summarize or review academic papers is itself a problem, as noted by Timothée Poisot, ...

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

The Large Hadron Collider is one of the biggest experiments in history, but it’s also one of the hardest to interpret. Unlike ...

As higher ed institutions embrace generative artificial intelligence tools, Stony Brook University’s library is spearheading ...

Machine Learning with Omics Data Health research is increasingly turning to high-throughput molecular datasets (also known as ‘omic’ datasets) to discover novel biomarkers of disease risk and outcome.

I expect that within five years we will all have the option of a smart, always available, personal assistant. A good model ...

Long before a customer reads a tagline or hears a jingle, she sees colour. Research has it that nearly 90% of snap judgments ...

The story of bringing dire wolves back from extinction begins not in a laboratory, but in ancient deposits where their remains lay buried for millennia. The genetic material that would eventually give ...

Sharks themselves, apex predators honed over hundreds of millions of years, are now among the most imperiled inhabitants of ...

This repository contains datasets for multi-object representation learning, used in developing scene decomposition methods like MONet [1], IODINE [2], and SIMONe [3]. The datasets we provide are: ...