Partial multi-view clustering. In: Proceedings of the AAAI conference on artificial intelligence. 2014. p. 28. Wen J, Zhang Z, Xu Y, Zhong Z. Incomplete multi-view clustering via graph regularized matrix factor
Generative Partial Visual-Tactile Fused Object Clustering.Tao ZhangYang CongGan SunJiahua DongYuyang LiuZhengming DingNational Conference on Artificial Intelligence
Multi-facet clustering variational autoencoders. Adv. Neural Inf. Process. Syst. 34, 8676–8690 (2021). Google Scholar Fortuin, V., Hüser, M., Locatello, F., Strathmann, H. & Rätsch, G. SOM-VAE: interpretable discrete representation learning on time series. In International ...
This requires the reconstruction of a 3D scene from an input image (or a set of multi-view images), whereby the contents of the image(s) are causally explained in terms of models of instantiated objects, each with their own type, shape, appearance and pose, along with global variables ...
‘decodes’ latent variables back to sensory experience. In psychological terms, after training on a class of stimuli, VAEs can reconstruct such stimuli from a partial input according to the schema for that class, and generate novel stimuli consistent with the schema. (Our use of VAEs is ...
Ensemble deep learning of embeddings for clustering multimodal single-cell omics data. Bioinformatics 2023:btad382. Liu Q, Song K. ProgCAE: a deep learning-based method that integrates multi-omics data to predict cancer subtypes. Brief Bioinform 2023:bbad196. Chai H, Zhou X, Zhang Z, Rao ...
MUNIT (Huang et al., 2018) Multi-modal unsupervised image-to-image translation SAGAN (Zhang et al., 2019a) Self-attention GAN ClusterGAN (Mukherjee et al., 2019) Clustering GAN Rev-GAN (van der Ouderaa and Worrall, 2019) Reversible GAN StyleGAN (Karras et al., 2019) Style-transfer GAN...
(Fig.2c). When we trained siVAE and provided batch information during training, clustering by batch is eliminated while the clustering by cell type is still preserved (Fig.2d). These results suggest that siVAE is a viable alternative to existing dimensionality reduction approaches that can be ...
offering profound insights into cellular identity and function. Effective integration of the multi-omics data produces cell embeddings crucial for diverse analyses. These embeddings are pivotal for precise cell clustering and identification, and they support numerous downstream tasks. Metrics such as the ...
Ran, A. et al. Fast clustering of retired lithium-ion batteries for secondary life with a two-step learning method.ACS Energy Lett.7, 3817–3825 (2022). ArticleCASGoogle Scholar Lai, X. et al. Rapid sorting and regrouping of retired lithium-ion battery modules for echelon utilization based...