Information-controlled graph convolutional network for multi-view semi-supervised classification.

Graph convolutional networks have achieved remarkable success in the field of multi-view learning. Unfortunately, most graph convolutional network-based multi-view learning methods fail to capture long-range dependencies due to the over-smoothing problem. Many studies have attempted to mitigate this issue by decoupling graph convolution operations.

Inhomogeneous Diffusion-Induced Network for Multiview Semi-Supervised Classification.

The challenges posed by heterogeneous data in practical applications have made multiview semi-supervised classification a focus of attention for researchers. While several graph-based approaches have been suggested for this task, they tend to use homogeneous feature propagation, leading to even diffusion of node information to their neighbors. However, this diffusion strategy results in nodes acquiring information of equal proportion from dissimilar samples.

UMCGL: Universal Multi-View Consensus Graph Learning With Consistency and Diversity.

Existing multi-view graph learning methods often rely on consistent information for similar nodes within and across views, however they may lack adaptability when facing diversity challenges from noise, varied views, and complex data distributions. These challenges can be mainly categorized into: 1) View-specific diversity within intra-view from noise and incomplete information; 2) Cross-view diversity within inter-view caused by various latent semantics; 3) Cross-group diversity within inter-group due to data distribution differences. To this end, we propose a universal multi-view consensus graph learning framework that considers both original and generative graphs to balance consistency and diversity.

Capillary-Bridge Controlled Patterning of Stable Double-Perovskite Microwire Arrays for Non-toxic Photodetectors.

Single-crystalline lead halide perovskites with remarkable physical properties offer great potential in integrated optoelectronic applications but are restricted by their instability and toxicity. To address these problems, various strategies including lead-free halide double perovskites with high stabilities of heat, light, and moisture have been developed. However, it still requires an efficient method to pattern single-crystalline, double-perovskite micro-/nanostructures with strict alignment and ordered orientation for the integration of optoelectronic devices.

Highly Ordered Semiconducting Polymer Arrays for Sensitive Photodetectors.

Semiconducting conjugated polymers possess attractive optoelectronic properties and low-cost solution processability and are inherently mechanically flexible. However, the device performance is susceptible to the fabrication methods because of the relatively weak intermolecular interaction of the polymers and their inherent conformational and energetic disorder. An efficient fabrication technique for large-scale integration of high-quality polymer architectures is essential for realizing high-performance optoelectronic devices.