eLife

Separating selection from mutation in antibody language models

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 ...
eLife

Decision-making components and times revealed by the single-trial electroencephalogram

By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...
thorax.bmj

Development and validation of PRECISE-X model: predicting first severe exacerbation in COPD

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...
IEEE

A Conditional Denoising Diffusion Probabilistic Model for Sea Ice Concentration Estimation

Abstract: Research on estimating sea ice concentration (SIC) from synthetic aperture radar (SAR) data using convolutional neural networks (CNNs) has been widely reported. However, the presence of ...

New framework helps climate modelers integrate Indigenous community input into simulations

Advanced computer models can quantify the impacts of climate change and other environmental challenges, providing deep ...
IEEE

Complex-valued Conditional Diffusion Model with Physical Scattering Information for SAR Image Target Recognition

Abstract: Deep learning-based methods require samples for training, while synthetic aperture radar (SAR) images are limited due to the imaging environment, which restricts the recognition performance ...