A universal fault-tolerant quantum computer that can efficiently solve problems such as
integer factorization and unstructured database search requires millions of qubits with low …

In recent years, the use of machine learning (ML) in computational chemistry has enabled
numerous advances previously out of reach due to the computational complexity of …

We develop FinBERT, a state‐of‐the‐art large language model that adapts to the finance
domain. We show that FinBERT incorporates finance knowledge and can better summarize …

The advent of the World Wide Web and the rapid adoption of social media platforms (such
as Facebook and Twitter) paved the way for information dissemination that has never been …

Recent years include the world's hottest year, while they have been marked mainly, besides
the COVID-19 pandemic, by climate-related disasters, based on data collected by the …

Audio signals generated by the human body (eg, sighs, breathing, heart, digestion, vibration
sounds) have routinely been used by clinicians as indicators to diagnose disease or assess …

Transformers are state-of-the-art models for a variety of sequence modeling tasks. At their
core is an attention function which models pairwise interactions between the inputs at every …

Electronically excited states of molecules are at the heart of photochemistry, photophysics,
as well as photobiology and also play a role in material science. Their theoretical description …

Machine learning (ML) encompasses a broad range of algorithms and modeling tools used
for a vast array of data processing tasks, which has entered most scientific disciplines in …

Machine learning methods have been remarkably successful for a wide range of application
areas in the extraction of essential information from data. An exciting and relatively recent …