Results 51 to 60 of about 27,772 (256)
eLife, 2023 Multivariable Mendelian randomisation (MVMR) is an instrumental variable technique that generalises the MR framework for multiple exposures. Framed as a regression problem, it is subject to the pitfall of multicollinearity.
Vasileios Karageorgiou +3 more
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Sparse PCA via Bipartite Matchings
CoRR, 2015 We consider the following multi-component sparse PCA problem: given a set of data points, we seek to extract a small number of sparse components with disjoint supports that jointly capture the maximum possible variance. These components can be computed one by one, repeatedly solving the single-component problem and deflating the input data matrix, but ...
Megasthenis Asteris +3 more
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Advanced Healthcare Materials, EarlyView.Dynamic compression enhances mesenchymal stromal cell proliferation in nonwoven PET scaffolds under chondrogenic differentiation conditions and triggers mechanosensitive transcriptional programs associated with extracellular matrix remodeling. These findings highlight the potential of mechanically stimulated PET scaffolds as a promising platform for ...
Graciosa Quelhas Teixeira +8 more
wiley +1 more source
Sparse PCA Beyond Covariance Thresholding
CoRR, 2023 In the Wishart model for sparse PCA we are given $n$ samples $Y_1,\ldots, Y_n$ drawn independently from a $d$-dimensional Gaussian distribution $N({0, Id + βvv^\top})$, where $β> 0$ and $v\in \mathbb{R}^d$ is a $k$-sparse unit vector, and we wish to recover $v$ (up to sign).
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On‐Chip Photonic Neural Network Architectures
Advanced Optical Materials, EarlyView.This review presents a comprehensive overview of on‐chip photonic neural network architectures, covering key photonic building blocks, representative network types, and emerging applications. Recent advances, implementation challenges, and future directions are examined, highlighting the potential of integrated photonics to enable ultrafast, energy ...
Seokjin Hong +7 more
wiley +1 more source
Rational Polynomial Coefficient Estimation via Adaptive Sparse PCA-Based Method
Remote SensingThe Rational Function Model (RFM) is composed of numerous highly correlated Rational Polynomial Coefficients (RPCs), establishing a mathematical relationship between two-dimensional images and three-dimensional spatial coordinates.
Tianyu Yan, Yingqian Wang, Pu Wang
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Sparse Kernel PCA for Outlier Detection
2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), 2018 Accepted at IEEE ICMLA 2018 for Oral ...
Rudrajit Das +2 more
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Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges
Advanced Robotics Research, EarlyView.This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder +3 more
wiley +1 more source
Deep Contrastive Learning for High‐Throughput Prediction of Drug Resistance Mutations from Sequences
Advanced Science, EarlyView.This study presents DeepMutDTA, a deep learning framework aimed at predicting mutation‐induced changes in protein‐drug interactions and prioritizing variants potentially linked to drug resistance. Trained on large‐scale data, it incorporates SimSiam‐MuTF, a label‐aware contrastive fine‐tuning strategy that encourages separation between WT and MT ...
Xiaowen Hu +7 more
wiley +1 more source
Sparse PCA via Covariance Thresholding
J. Mach. Learn. Res., 2013 40 pages, 3 figures ...
Yash Deshpande, Andrea Montanari
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