Results 41 to 50 of about 1,248,103 (272)
Representation of self-similar Gaussian processes [PDF]
, 2014 We develop the canonical Volterra representation for a self-similar Gaussian process by using the Lamperti transformation of the corresponding stationary Gaussian process, where this latter one admits a canonical integral representation under the ...
Yazigi, Adil
core +1 more source
Molecular Oncology, EarlyView.Development of therapies targeting cancer‐associated fibroblasts (CAFs) necessitates preclinical model systems that faithfully represent CAF–tumor biology. We established an in vitro coculture system of patient‐derived pancreatic CAFs and tumor cell lines and demonstrated its recapitulation of primary CAF–tumor biology with single‐cell transcriptomics ...
Elysia Saputra +10 more
wiley +1 more source
Gaussian Process Prior Variational Autoencoders [PDF]
, 2018 Variational autoencoders (VAE) are a powerful and widely-used class of models to learn complex data distributions in an unsupervised fashion. One important limitation of VAEs is the prior assumption that latent sample representations are independent and ...
Casale, Francesco Paolo +4 more
core +1 more source
FEBS Open Bio, EarlyView.Unique biological samples, such as site‐specific mutant proteins, are available only in limited quantities. Here, we present a polarization‐resolved transient infrared spectroscopy setup with referencing to improve signal‐to‐noise tailored towards tracing small signals. We provide an overview of characterizing the excitation conditions for polarization‐
Clark Zahn, Karsten Heyne
wiley +1 more source
Gaussian Process Graph-Based Discriminant Analysis for Hyperspectral Images Classification
Remote Sensing, 2019 Dimensionality Reduction (DR) models are highly useful for tackling Hyperspectral Images (HSIs) classification tasks. They mainly address two issues: the curse of dimensionality with respect to spectral features, and the limited number of labeled ...
Xin Song +3 more
doaj +1 more source
Variations and estimators for the selfsimilarity order through Malliavin calculus
, 2009 Using multiple stochastic integrals and the Malliavin calculus, we analyze the asymptotic behavior of quadratic variations for a specific non-Gaussian self-similar process, the Rosenblatt process. We apply our results to the design of strongly consistent
Tudor, Ciprian, Viens, Frederi
core +5 more sources
Single‐molecule DNA flow‐stretch assays for high‐throughput DNA–protein interaction studies
FEBS Open Bio, EarlyView.We describe an optimised single‐molecule DNA flow‐stretch assay that visualises DNA–protein interactions in real time. Linear DNA fragments are tethered to a surface and stretched by buffer flow for fluorescence imaging. Using λ and φX174 DNA, this protocol enhances reproducibility and accessibility, providing a versatile approach for studying diverse ...
Ayush Kumar Ganguli +8 more
wiley +1 more source
Gaussian Process Regression with Mismatched Models [PDF]
, 2001 Learning curves for Gaussian process regression are well understood when the `student' model happens to match the `teacher' (true data generation process). I derive approximations to the learning curves for the more generic case of mismatched models, and
Sollich, Peter
core +1 more source
FEBS Open Bio, EarlyView.Amino acids sequence of two different proteins with the same sequence (chameleon sequence—black boxes) represent in 3D structure of the proteins different secondary structures: HHHH—helical and BBB—Beta‐structural. The chains folded in water environment adopt different III‐order structures in which the chameleon fragments appear to adopt similar status
Irena Roterman +4 more
wiley +1 more source
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source