Results 61 to 70 of about 225,245 (281)
HLoOP—Hyperbolic 2-Space Local Outlier Probabilities
Hyperbolic geometry has recently garnered considerable attention in machine learning due to its ability to embed hierarchical graph structures with low distortions for further downstream processing.
Clemence Allietta +3 more
doaj +1 more source
Automatic Detection of Outliers in Multibeam Echo Sounding Data [PDF]
The data volumes produced by new generation multibeam systems are very large, especially for shallow water systems. Results from recent multibeam surveys indicate that the ratio of the field survey time, to the time used in interactive editing through ...
Hou, Tianhang +2 more
core +1 more source
A Robust Adaptive Stochastic Gradient Method for Deep Learning
Stochastic gradient algorithms are the main focus of large-scale optimization problems and led to important successes in the recent advancement of the deep learning algorithms. The convergence of SGD depends on the careful choice of learning rate and the
Bengio, Yoshua +3 more
core +1 more source
Complementarity of Long‐Reads and Optical Mapping in Parkinson's Disease for Structural Variants
ABSTRACT Objective Long‐read sequencing and optical genome mapping technologies have the ability to detect large and complex structural variants. This has led to the discovery of novel pathogenic variants in neurodegenerative movement disorders. Thus, we aimed to systematically compare the SV detection capabilities of OGM and ONT in Parkinson's disease.
André Fienemann +17 more
wiley +1 more source
A fluctuation test for constant Spearman's rho with nuisance-free limit distribution
A CUSUM type test for constant correlation that goes beyond a previously suggested correlation constancy test by considering Spearman's rho in arbitrary dimensions is proposed.
Dehling, Herold +3 more
core +1 more source
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley +1 more source
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Crowdsourced correlation clustering with relative distance comparisons
Crowdsourced, or human computation based clustering algorithms usually rely on relative distance comparisons, as these are easier to elicit from human workers than absolute distance information.
Ukkonen, Antti
core +1 more source
A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice +2 more
wiley +1 more source
MXene dervied CoFe composites show increased initial Oxygen Evolution Reaction (OER) activity compared to the pure CoFe and MXene in an Anion Exchange Membrane device. Vanadium vacancies in the MXene plays a role in increased OER activity and hinders Fe leaching in the AEM device over using the pure V2C MXene as a support material for the CoFe ...
Can Kaplan +16 more
wiley +1 more source

