Results 81 to 90 of about 105,297 (262)

Few-Shot Graph Anomaly Detection via Dual-Level Knowledge Distillation

open access: yesEntropy
Graph anomaly detection is crucial in many high-impact applications across diverse fields. In anomaly detection tasks, collecting plenty of annotated data tends to be costly and laborious.
Xuan Li   +4 more
doaj   +1 more source

Cross-subject brain entropy mapping

open access: yes
AbstractWe present a method to map the regional similarity between resting state fMRI activities of different individuals. The similarity was measured using cross-entropy. Group level patterns were displayed based on the Human Connectome Project Youth data.
Del Mauro, G., Wang, Z.
openaire   +2 more sources

RIPK4 function interferes with melanoma cell adhesion and metastasis

open access: yesMolecular Oncology, EarlyView.
RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski   +9 more
wiley   +1 more source

Engineered extracellular vesicles enriched with the miR‐214/199a cluster enhance the efficacy of chemotherapy in ovarian cancer

open access: yesMolecular Oncology, EarlyView.
Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang   +12 more
wiley   +1 more source

Explicit Model for Chiller Fault Diagnosis Based on Multi-objective Regression with Different Weights

open access: yesZhileng xuebao
Based on the cross-entropy loss function and stochastic gradient descent algorithm, a weight regression fault diagnosis model was established for seven common faults in a chiller.
Wu Kongrui   +4 more
doaj  

Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer

open access: yesMolecular Oncology, EarlyView.
COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann   +61 more
wiley   +1 more source

Combined Forecasting of Streamflow Based on Cross Entropy

open access: yesEntropy, 2016
In this study, we developed a model of combined streamflow forecasting based on cross entropy to solve the problems of streamflow complexity and random hydrological processes.
Baohui Men, Rishang Long, Jianhua Zhang
doaj   +1 more source

Deciphering transcriptional plasticity in pancreatic ductal adenocarcinoma reveals alterations in sensory neuron innervation

open access: yesMolecular Oncology, EarlyView.
Pancreatic sensory neurons innervating healthy and PDAC tissue were retrogradely labeled and profiled by single‐cell RNA sequencing. Tumor‐associated innervation showed a dominant neurofilament‐positive subtype, altered mitochondrial gene signatures, and reduced non‐peptidergic neurons.
Elena Genova   +14 more
wiley   +1 more source

Some Order Preserving Inequalities for Cross Entropy and Kullback–Leibler Divergence

open access: yesEntropy, 2018
Cross entropy and Kullback⁻Leibler (K-L) divergence are fundamental quantities of information theory, and they are widely used in many fields. Since cross entropy is the negated logarithm of likelihood, minimizing cross entropy is equivalent to ...
Mateu Sbert   +3 more
doaj   +1 more source

Taming the Cross Entropy Loss [PDF]

open access: yes, 2019
We present the Tamed Cross Entropy (TCE) loss function, a robust derivative of the standard Cross Entropy (CE) loss used in deep learning for classification tasks. However, unlike other robust losses, the TCE loss is designed to exhibit the same training properties than the CE loss in noiseless scenarios.
Martinez, Manuel, Stiefelhagen, Rainer
openaire   +3 more sources

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