PNAS

Predictions from deep learning propose substantial protein–carbohydrate interplay

The totality of the protein–carbohydrate interactome remains elusive, in part due to the inability to directly probe a proteome versus a glycome in a high throughput manner. Here we show a ...
GitHub

Flash LiDAR Vehicle Detection with MATLAB Dataset and Deep Learning Benchmarks

This repository provides code and workflows to test several state-of-the-art vehicle detection deep learning algorithms —including YOLOX, SalsaNext, and RandLA-Net— on a Flash Lidar dataset. The ...
Frontiers

Genetic risk predictions using deep learning models with summary data

As a driving force of the Fourth Industrial Revolution, deep learning methods have achieved significant success across various fields, including genetic and genomic studies. While individual-level ...
KCEN TV

TEAM CANADA WORLD JUNIORS ROSTER PREDICTIONS | Loads of Talent, Who Makes the Cut?

TEAM CANADA WORLD JUNIORS ROSTER PREDICTIONS | Loads of Talent, Who Makes the Cut? To stream 6 News on your phone, you need the 6 News app.
IEEE

Short-term Load Prediction in Federated Learning Industrial Parks Based on Attention ...

Abstract: The current industrial load demand is huge in scale and complex in power consumption characteristics. The deep learning prediction model built has difficulty in feature extraction leading to ...
PNAS

A protein dynamics–based deep learning model enhances predictions of fitness and epistasis

Predicting the effects of multiple mutations on protein function is challenging due to the intricate interplay between residues. Machine learning has advanced these efforts, but traditional neural ...
ahajournals.org

Prediction of Atrial Fibrillation From the ECG in the Community Using Deep Learning: A ...

We aimed to refine and validate a deep neural network model from the ECG to predict atrial fibrillation (AF) risk, using samples from diverse backgrounds: the Framingham Heart Study (FHS), UK Biobank, ...
Frontiers

Enhancing disaster prediction with Bayesian deep learning: a robust approach for ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...