This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...

This is where the spelling debate gets more interesting. When we talk about AI, for instance, does "high tech" still capture ...

Abstract: Traditional machine learning approaches assume that data comes from a single generating mechanism, which may not hold for most real life data. In these cases, the single mechanism assumption ...

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

If there is one skill that sits at the heart of most successful AI and machine learning projects today, it is Python. Whether a company wants to build smarter automation, design predictive solutions, ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

RPG Larian's head writer has a simple answer for how AI-generated text helps development: 'It doesn't,' thanks to its best output being 'a 3/10 at best' worse than his worst drafts Graphics Cards 'It ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

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