Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

Here’s how: prior to the transformer, what you had was essentially a set of weighted inputs. You had LSTMs (long short term memory networks) to enhance backpropagation – but there were still some ...

A machine-learning loop searched 14 million battery cathode compositions and found fivefold performance gains across four metrics using fewer than 200 experiments.

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20100 ...

The field of particle physics is approaching a critical horizon defined by challenges including unprecedented data volumes and detector complexity. Upcoming ...

In biomedical modeling, the integration of mechanistic and data-driven approaches is reshaping how we interpret and predict complex biological phenomena.

Umbrella or sun cap? Buy or sell stocks? When it comes to questions like these, many people today rely on AI-supported recommendations. Chatbots such as ChatGPT, AI-driven weather forecasts, and ...

The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

A brisk theatrical thriller, “Data” perfectly captures the slick, grandiose language with which tech titans justify their ...

Abstract: This study aims to compare the performance of five different models for spelling error detection, a crucial task in natural language processing. In this ...