https://pubmed.ncbi.nlm.nih.gov/38091758
This abstract is a correction notice for the paper “Lower and upper bounds for numbers of linear regions of graph convolutional networks,” adjusting errors in the original publication.
https://pubmed.ncbi.nlm.nih.gov/38091758
This abstract is a correction notice for the paper “Lower and upper bounds for numbers of linear regions of graph convolutional networks,” adjusting errors in the original publication.
https://pubmed.ncbi.nlm.nih.gov/38091757
This study proposes a method for document-level relation extraction that uses relation co-occurrence correlation to address the long-tail and multi-label challenges, and demonstrates its superior performance on two popular datasets.
https://pubmed.ncbi.nlm.nih.gov/38091756
The abstract describes a new method for creating adversarial attacks on video classification models, called DeepSAVA, which uses a sparse perturbation strategy and structural similarity index to maintain human imperceptibility while achieving high attack success rate and adversarial transferability. The method can also be used to improve the robustness of video classification models through adversarial training.
https://pubmed.ncbi.nlm.nih.gov/38091755
This study, “Adaptive-weighted deep Multi-view Clustering with Uniform scale representation (AMCU),” introduces a joint learning framework that adaptively weighs the importance of multiple views and regularizes learned latent representations to have a uniform scale, leading to improved clustering performance compared to several state-of-the-art methods on eight real-world datasets.
https://pubmed.ncbi.nlm.nih.gov/38091754
This study, “Towards performance-maximizing neural network pruning via global channel attention,” presents a novel static channel pruning method, GlobalPru, that outperforms existing state-of-the-art static and dynamic pruning methods on ImageNet, SVHN, and CIFAR-10/100 datasets by using a channel attention-based learn-to-rank framework to create a global ranking of channels and share it across different data.
https://pubmed.ncbi.nlm.nih.gov/38091753
In this study, the authors demonstrate that energy dynamics controlled by spatial electromagnetic radiation can predict wave propagation and synchronization in a memristive neural network.
https://pubmed.ncbi.nlm.nih.gov/38091751
This study found that white matter integrity differs between individuals with MAPT mutations and non-carrier family controls, with the most significant differences involving fronto-temporal white matter tracts, and increasing abnormalities found as the estimated time to or from disease onset progresses.
https://pubmed.ncbi.nlm.nih.gov/38091750
Two fluorescent probes have been developed to visualize the transformation of nonalcoholic fatty liver to nonalcoholic steatohepatitis in liver orthotopic imaging by detecting changes in carboxylesterase and peroxynitrite.
https://pubmed.ncbi.nlm.nih.gov/38091749
A novel, rapid, and specific assay for β-etherase activity has been developed using a newly synthesized chromogenic substrate, enabling the monitoring of enzymes involved in lignin valorization.