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Last Updated: 22 September 2022

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Spurious Local Minima Are Common for Deep Neural Networks With Piecewise Linear Activations.

It is shown in this article that spurious local minima are common for deep connected networks and average-pooling convolutional neural networks with piecewise linear activations and datasets that cannot be represented by linear models. Motivating evidence is given to show why spurious local minima exist: each output neuron of ubiquitously connected networks and CNNs with piecewise linear code activations provides a continuous piecewise linear function, and various CPWL modules can precisely fit disjoint groups of data samples when minimizing the empirical risk.

Source link: https://doi.org/10.1109/TNNLS.2022.3204319


Binary Mixtures in Linear Convection Arrays.

These procedures are quantitatively characterized by investigating the influence of the active and passive particles' diffusion constants on the parameters of the active mixture fraction.

Source link: https://doi.org/10.1002/cphc.202200471


Machine unlearning: linear filtration for logit-based classifiers.

Machine learning is a challenge to machine learning: what to do if an individual retracts permission to use data that has not been part of a model's preparation process? The field of machine unlearning, which could be broadly defined as the inquiry into how to 'delete modeling results from models,'" comes from this curiosity.

Source link: https://doi.org/10.1007/s10994-022-06178-9


Highly emissions of TPA-linear based pyrazine derivatives with different mechanochromic luminosity.

We created TPA-based linear pyrazine derivatives of PP-1 and PP-2, which were synthesized using the common Suzuki cross-linking reaction. The transition was gradually reduced as a result of the non-polar aprotic solvent to the polar aprotic solvent, resulting in a red shift. In addition, the Aggregation-induced emission effect has been investigated in relation to the DMF/water addition of linear pyrazine compounds. A blue shift and a mild AIE effect have occurred in this case, after this case, when the water content in these studies was increased by 50 percent to 90 percent. Using TFA acid, was also investigated the acidochromic effect of compounds PP-1 and PP-2.

Source link: https://doi.org/10.1016/j.saa.2022.121874


A quantile integral linear model to quantify genetic effects on phenotypic variability.

Detecting genetic variants linked to the diversity of complex traits, i. e. variance quantitative trait loci, can provide important insights into the interplay between genes and environments, as well as how human phenotypes in the population. To determine genetic effects on trait variation, we recommend a quantitative integral linear model. Applied to UK Biobank, QUAIL reported 11 vQTLs for body mass index that had not been reported before. In addition, variance polygenic scores based on QUAIL effect estimates provided superior predictive results on both population level and within-individual BMI variability, in comparison to previous methods.

Source link: https://doi.org/10.1073/pnas.2212959119


Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI with Sparse Sampling.

Dynamic resonance imaging's spatial resolution and temporal framerate can be enhanced by reconstructing images from sparsely sampled k-space data with mathematical simulation of the underlying spatiotemporal data. This paper introduces a new linear tangent space alignment model-based framework that exploits the inherent low-dimensional manifold structure of dynamic images for enhanced dynamic MRI. Out of all of the compared methods, the new technique gave the highest success in image reconstruction.

Source link: https://doi.org/10.1109/TMI.2022.3207774


Numerical Approximation of the Nonequilibrium Model of Gradient Elution Chromatography Considering Linear and Nonlinear Solvent Strength Models.

When appropriate equilibrium values and mass transfer coefficients are available, the lumped kinetic model is a good start for forecasting elution bands in both linear and nonlinear chromatography. Changes in the equilibrium parameters due to changes in the mobile phase composition are known, and this model also works well in the case of gradient elution chromatography. In this research, three new perspectives using the lumped kinetic model are explored. In this research, the pragmatic selection of an optimal gradient is investigated.

Source link: https://doi.org/10.1021/acsomega.2c02754


LANet: Stereo matching network based on linear-attention mechanism for depth estimation optimization in 3D reconstruction of inter-forest scene.

The 3D reconstruction of forests provides a solid basis for scientific control of tree growth and fine survey of forest resources. LANet, a stereo matching network based on Linear-Attention's method, is designed to solve the problem that the current stereo matching schemes lack the ability to use environmental data to determine the consistency of ill-posed regions, resulting in poor matching results in regions with poor texture, occlusion, and other insignificant characteristics, thereby optimizing the depth estimation effect. An AM attention module with a spatial awareness module and a channel attention module is designed to represent the semantic relevance of inter-forest scenes from the spatial and channel dimensions. The Self-Attention device in CAM specifically emphasizes interdependence channel maps by learning the pertinent attributes of various channels.

Source link: https://doi.org/10.3389/fpls.2022.978564


Generalized linear mixed-effects models for studies using different sets of stimuli across conditions.

A non-repeated article design refers to an experimental setup in which products used in one level of experimental conditions are not used consistently at other levels. The latest research has suggested the use of generalized linear mixed-effects models for experimental data analysis, but the existing GLMMs model does not account for any potential dependencies among the results in NRI studies. When the item effect's variance was heterogeneous, the model with a level-specific item random effect performed better than the current model in terms of power.

Source link: https://doi.org/10.3389/fpsyg.2022.955722

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions