Results 11 to 20 of about 12,789,197 (342)
Accurate prediction of protein structures and interactions using a 3-track neural network
Science, 2021 Deep learning takes on protein folding In 1972, Anfinsen won a Nobel prize for demonstrating a connection between a protein's amino acid sequence and its three-dimensional structure.
B. M +31 more
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LINE: Large-scale Information Network Embedding [PDF]
The Web Conference, 2015 This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction.
Jian Tang +5 more
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Residual Dense Network for Image Super-Resolution [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018 A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well.
Yulun Zhang +4 more
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Наука телевидения, 2021 There are numerous empirical sociological researches of transmedia storytelling media consumption. However, they mainly record either the practices of media consumption of specific media formats included in the structure of a transmedia project or the ...
MILOVIDOV STANISLAV V. / МИЛОВИДОВ С.В.
doaj +1 more source
, 2004 We consider the categorical concepts of a ‘network of networks’: (a) each node is a host network (1-network or 1-graph) and super-links are analogous to a graph-functor, i.e. this is (1,1)-network; (b) 2-network where there are 2-links among 1-links. The general notion of network-morphism is proposed.
José de Jesús Cruz Guzmán +1 more
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SCENIC: Single-cell regulatory network inference and clustering
Nature Methods, 2017 We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic.aertslab.org).
S. Aibar +13 more
semanticscholar +1 more source
Learning Deconvolution Network for Semantic Segmentation [PDF]
IEEE International Conference on Computer Vision, 2015 We propose a novel semantic segmentation algorithm by learning a deep deconvolution network. We learn the network on top of the convolutional layers adopted from VGG 16-layer net.
Hyeonwoo Noh +2 more
semanticscholar +1 more source
Frontiers in Marine Science, 2023 Climate change is threatening marine ecosystems and the distribution of species which rely on them. Due to their capacity to sequester vast amounts of carbon, blue carbon ecosystems (BCEs; seagrass, mangroves, salt marshes, kelp forests) are becoming ...
Olivia F. L. Dixon, Austin J. Gallagher
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Robustness of a Network of Networks [PDF]
Physical Review Letters, 2011 Almost all network research has been focused on the properties of a single network that does not interact and depends on other networks. In reality, many real-world networks interact with other networks. Here we develop an analytical framework for studying interacting networks and present an exact percolation law for a network of $n$ interdependent ...
Jianxi Gao +3 more
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Heterogeneous Graph Attention Network [PDF]
The Web Conference, 2019 Graph neural network, as a powerful graph representation technique based on deep learning, has shown superior performance and attracted considerable research interest.
Xiao Wang +6 more
semanticscholar +1 more source