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Found 5 papers, 2 papers with code
Derivative-Free Optimization for Low-Rank Adaptation in Large Language Models
Parameter-efficient tuning methods such as LoRA could achieve comparable performance to model tuning by tuning a small portion of the parameters.
Plug-and-Play Latent Feature Editing for Orientation-Adaptive Quantitative Susceptibility Mapping Neural Networks
The proposed OA-LFE-empowered iQSM, which we refer to as iQSM+, is trained in a self-supervised manner on a specially-designed simulation brain dataset.
Quantitative Susceptibility Mapping through Model-based Deep Image Prior (MoDIP)
The data-driven approach of supervised learning methods has limited applicability in solving dipole inversion in Quantitative Susceptibility Mapping (QSM) with varying scan parameters across different objects.
Associating Multi-Scale Receptive Fields for Fine-grained Recognition
First, CNL computes correlations between features of a query layer and all response layers.
On the Generalization Effects of DenseNet Model Structures
Modern neural network architectures take advantage of increasingly deeper layers, and various advances in their structure to achieve better performance.
