Results 91 to 100 of about 36,894 (295)
Advanced Healthcare Materials, EarlyView.A miniaturized drug sensitivity and resistance testing (DSRT) workflow based on the Droplet Microarray (DMA) platform enables functional drug testing using minimal patient‐derived tumor material. By screening nanoliter‐scale droplets containing as few as 300 cells, this approach generates reproducible and tumor‐specific drug response profiles ...
Maryam Salarian +7 more
wiley +1 more source
Manifold Learning From Time Series
, 2006 This thesis addresses the problem of learning manifold from time series. We use the mixtures of probabilistic principal component analyzers (MPPCA) to model the nonliner manifold. In addition, we extend the MPPCA model by aligning the PCA coe.cients from
Lin, Ruei-Sung
core +1 more source
Unsupervised shape clustering using diffusion map [PDF]
, 2008 The quotient space of all smooth and connected curves represented by a fixed number of boundary points is a finite-dimensional Riemannian manifold, also known as a shape manifold.
Rajpoot, Nasir M. (Nasir Mahmood) +1 more
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Advanced Healthcare Materials, EarlyView.PolyGraph, a flexible graphene‐polycaprolactone nanocomposite, unites conductivity, biocompatibility, and processability for next‐generation neural interfaces. Fabricated into microneedle arrays with ultra‐flexible backings, PolyGraph enables bidirectional neuronal recording and stimulation in brain tissue, advancing brain‐computer interface (BCI) and ...
Jack Maughan +12 more
wiley +1 more source
The similarity between objects is a fundamental element of many learning algorithms. Most non-parametric methods take this similarity to be fixed, but much recent work has shown the advantages of learning it, in particular to exploit the local ...
Yoshua Bengio, Pascal Vincent
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Spectral Geometry for Structural Pattern Recognition [PDF]
, 2010 Graphs are used pervasively in computer science as representations of data with a network or relational structure, where the graph structure provides a flexible representation such that there is no fixed dimensionality for objects. However, the analysis
El Ghawalby, Heyayda +1 more
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All‐Optical Reconfigurable Physical Unclonable Function for Sustainable Security
Advanced Materials, EarlyView.An all‐optical reconfigurable physical unclonable function (PUF) is demonstrated using plasmonic coupling–induced sintering of optically trapped gold nanoparticles, where Brownian motion serves as a robust entropy source. The resulting optical PUF exhibits high encoding density, strong resistance to modeling attacks, and practical authentication ...
Jang‐Kyun Kwak +4 more
wiley +1 more source
Regularized manifold information extreme learning machine
Tongxin xuebao, 2016 By exploiting the thought of manifold learning and its theoretical method, a regularized manifold information ex-treme learning machine algorithm aimed to depict and fully utilize manifold information was proposed.
De-shan LIU, Yong-he CHU, De-qin YAN
doaj +2 more sources
Multi-view data visualisation via manifold learning [PDF]
PeerJ Computer ScienceNon-linear dimensionality reduction can be performed by manifold learning approaches, such as stochastic neighbour embedding (SNE), locally linear embedding (LLE) and isometric feature mapping (ISOMAP).
Theodoulos Rodosthenous +2 more
doaj +2 more sources
Algorithms for manifold learning [PDF]
, 2008 Manifold learning is a popular recent approach to nonlinear dimensionality reduction. Algorithms for this task are based on the idea that the dimensionality of many data sets is only artificially high; though each data point consists of perhaps ...
Cayton, Lawrence
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