The Manila Times

Chongwei Shi Advances Biostatistical Methods and Computational Biology Through Deep Learning and Statistical Shape Analysis

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
marktechpost

Building an Advanced Convolutional Neural Network with Attention for DNA Sequence Classification and Interpretability

In this tutorial, we take a hands-on approach to building an advanced convolutional neural network for DNA sequence classification. We focus on simulating real biological tasks, such as promoter ...
Scientific Research Publishing

Zhang, X., Zhao, J.B. and LeCun, Y. (2015) Character-Level Convolutional Networks for Text Classification.

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...
Frontiers

Convolutional neural networks decode finger movements in motor sequence learning from MEG data

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...
Frontiers

Enhanced deep Convolutional Neural Network for SARS-CoV-2 variants classification

Introduction: Rapid and scalable classification of SARS-CoV-2 genomes from spike-gene sequences can support real-time genomic surveillance in contexts where whole-genome data or high-end computing ...
Phys.org

Researchers develop neural network for large-scale celestial object classification

A new study led by researchers from the Yunnan Observatories of the Chinese Academy of Sciences has developed a neural network-based method for large-scale celestial object classification, according ...
IEEE

Behavioral Classification of Sequential Neural Activity Using Time Varying Recurrent Neural Networks

Abstract: Shifts in data distribution across time can strongly affect early classification of time-series data. When decoding behavior from neural activity, early detection of behavior may help in ...
IEEE

Reparameterized Feature Aggregation Convolutional Neural Network for Remote Sensing Scene Image Classification

Abstract: With the advancement of deep learning techniques, transformer has been introduced into remote sensing scene classification (RSSC). Although transformer performs well in building long-range ...
C&EN

Classification of Samples via Neural-Network Augmented Two-Dimensional Infrared Spectroscopy

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. The application of artificial neural network (ANN) techniques to spectroscopy has ...
techxplore

AI model based on neural oscillations delivers stable, efficient long-sequence predictions

Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence (AI) model inspired by neural oscillations in the brain, with the ...