Results 51 to 60 of about 875,579 (253)
, 2022 New implementations: Accumulative resampling strategies 1, see nmoo.algorithms.ARNSGA2; Gaussian process spectral sampling method described in 2, see nmoo.denoisers.GPSS. Fieldsend, J.E. (2015).
Cédric Ho Thanh, Stefan Klikovits
core +1 more source
FEBS Letters, EarlyView.Biomolecular condensates formed by fused in sarcoma (FUS) are dissolved by high ATP concentrations yet persist in cells. Using a reconstituted system, we demonstrate that valosin‐containing protein (VCP), an AAA+ ATPase, counteracts ATP‐driven dissolution of FUS condensates through its D2 ATPase activity.
Hitomi Kimura +2 more
wiley +1 more source
Design and analysis strategies for robust microbiome ageing research
FEBS Letters, EarlyView.The gut microbiome changes with age and associates with age‐related morbidity and mortality, establishing it as a potential biomarker and intervention target for ageing. Realising this potential requires methodological rigour, yet distinguishing biological signals from methodological artefacts remains challenging across cohorts. This review provides an
Mark Olenik +5 more
wiley +1 more source
Robust AUC optimization under the supervision of clean data
Scientific ReportsAUC (area under the ROC curve) is an essential metric that has been extensively researched in the field of machine learning. Traditional AUC optimization methods need a large-scale clean dataset, while real-world datasets usually contain massive noisy ...
Chenkang Zhang +3 more
doaj +1 more source
, 2023 Example of typical JV curve for solar cells, in dark and under ...
Nora M. Wilson (7505747)
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Investigating transcription factor dynamics in health and disease using FRAP
FEBS Letters, EarlyView.FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source
Scientific Reports, 2022 Neural networks (NNs) and linear stochastic estimation (LSE) have widely been utilized as powerful tools for fluid-flow regressions. We investigate fundamental differences between them considering two canonical fluid-flow problems: (1) the estimation of ...
Taichi Nakamura +2 more
doaj +1 more source
ScatterHough: Automatic Lane Detection from Noisy LiDAR Data
Sensors, 2022 Lane detection plays an essential role in autonomous driving. Using LiDAR data instead of RGB images makes lane detection a simple straight line, and curve fitting problem works for realtime applications even under poor weather or lighting conditions ...
Honghao Zeng +7 more
doaj +1 more source
Method of Moments for Estimation of Noisy Curves
SIAM Journal on Mathematics of Data ScienceIn this paper, we study the problem of recovering a ground truth high dimensional piecewise linear curve $C^*(t):[0, 1]\to\mathbb{R}^d$ from a high noise Gaussian point cloud with covariance $σ^2I$ centered around the curve. We establish that the sample complexity of recovering $C^*$ from data scales with order at least $σ^6$.
Phillip Lo, Yuehaw Khoo
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Delving into Sample Loss Curve to Embrace Noisy and Imbalanced Data
Proceedings of the AAAI Conference on Artificial Intelligence, 2022 Corrupted labels and class imbalance are commonly encountered in practically collected training data, which easily leads to over-fitting of deep neural networks (DNNs). Existing approaches alleviate these issues by adopting a sample re-weighting strategy, which is to re-weight sample by designing weighting function. However, it is only applicable for
Shenwang Jiang +5 more
openaire +3 more sources