6 papers · 1 filter
Enhancing Accuracy and Feature Insights in Hydration Free Energy Predictions for Small Molecules with Machine Learning
Mingjun Han, Yukai Zhang, Taotao Yu +3
The accurate prediction of solvation free energy is of significant importance as it governs the behavior of solutes in solution. In this work, we apply a variety of machine learnin…
Parameter Competition Balancing for Model Merging
Guodong Du, Junlin Lee, Jing Li +8
While fine-tuning pretrained models has become common practice, these models often underperform outside their specific domains. Recently developed model merging techniques enable t…
Impacts of Darwinian Evolution on Pre-trained Deep Neural Networks
Guodong Du, Runhua Jiang, Senqiao Yang +5
Darwinian evolution of the biological brain is documented through multiple lines of evidence, although the modes of evolutionary changes remain unclear. Drawing inspiration from th…
Evolutionary Neural Architecture Search for 3D Point Cloud Analysis
Yisheng Yang, Guodong Du, Chean Khim Toa +2
Neural architecture search (NAS) automates neural network design by using optimization algorithms to navigate architecture spaces, reducing the burden of manual architecture design…
Knowledge Fusion By Evolving Weights of Language Models
Guodong Du, Jing Li, Hanting Liu +5
Fine-tuning pre-trained language models, particularly large language models, demands extensive computing resources and can result in varying performance outcomes across different d…
CADE: Cosine Annealing Differential Evolution for Spiking Neural Network
Runhua Jiang, Guodong Du, Shuyang Yu +3
Spiking neural networks (SNNs) have gained prominence for their potential in neuromorphic computing and energy-efficient artificial intelligence, yet optimizing them remains a form…