Recent advances in spatial omics have expanded the spectrum of profiled molecular categories beyond transcriptomics. However, many of these technologies are constrained by limited spatial resolution, hindering our ability to deeply characterize intricate
(joint) latent space. Additionally, the generative part of the model provides a way to derive normalized, batch-corrected gene expression and accessibility values for both the multimodal cells (that is, normalizing the observed data) and for unpaired cells (that is, imputing unobserved data; Fig...
How generative and discriminative models work When algorithms are given large amounts of data to train a generative model, it’s used to help the algorithm identify structures and patterns that will help create new outputs. The generative model learns the probability distribution of these patterns ...
Bagal等[34]受生成式预训练新型神经网络模型(generative pre-training transformer,GPT)Transformer在生成文本任务中取得突破性进展的启发,基于GPT构建了一个新的生成模型MolGPT,能够根据给定条件(输入SMILES字符串、脂水分配系数、可合成性分...
Differential analysis of bulk RNA-seq data often suffers from lack of good controls. Here, we present a generative model that replaces controls, trained solely on healthy tissues. The unsupervised model learns a low-dimensional representation and can ide
deep learning representation learning deep generative model protein folding protein design Introduction Proteins are linear polymers that fold into various specific conformations to function. The incredible variety of three-dimensional (3D) structures determined by the combination and order in which 20 amino...
Here we present a comprehensive review concerning generative deep learning for data generation in natural hazard analysis. (1) We summarized the limitations associated with data availability in natural hazards analysis and identified the fundamental motivations for employing generative deep learning as a ...
clustering-based model:k-means,OCSVM,GMM,DBSCAN,k-prototypes, etc. 2. 深度学习 假设: 半监督学习:训练集均属于正常类。 多元数据:下述模型均能提取多元时间序列的信息。 深度学习算法分类 HTM,分层时间记忆网络;RNN,循环神经网络;TCN,时间卷积网络;GNN,图神经网络;GAN,生成对抗网络;VAE,变分自编码器。大多数...
A deep learning model is a neural network with many layers, which is able to learn from large amounts of data to do specific tasks. For a comprehensive review of deep learning techniques in medical imaging, we refer the reader to [108]. Convolutional neural networks (CNN), which are ...
We present a deep generative model of quantum optics experiments where a variational autoencoder is trained on a dataset of quantum optics experiment setups. In a series of computational experiments, we investigate the learned representation of our quantum optics variational autoencoder (QOVAE) and ...