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 ...
Scientific Research Publishing

Research on the Optimization Strategy of Integrating VR into Ideological and Political Courses in Colleges and Universities from the Perspective of College Students

Traditional VR instruction often places students directly into immersive experiences without preparation, resulting in a cognitive “cold start”. To resolve this issue, the first step in the ...
Scientific Research Publishing

Vanishing Gradients in an Artificial Deep Neural Network: The Impact of Activation Functions and Optimization Techniques ()

Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...
IEEE

Distributed Deep Reinforcement Learning for Ackermann Multi-Robot Formation: A Weighted Multi-Objective Optimization

Abstract: The integration of Internet of Things (IoT) with the multi-robot formation problem has been successfully applied in autonomous vehicles, unmanned aerial vehicles (UAVs), and industrial ...
IEEE

Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes

Abstract: Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of ...
C&EN

Bio-Digital Catalyst Design: Generative Deep Learning for Multi-Objective Optimization and Chemical Insights in CO

School of Chemistry and Chemical Engineering, Hefei University of Technology, Hefei 230009, China Anhui Province Key Laboratory of Value-Added Catalytic Conversion and Reaction Engineering, Hefei ...