Results 91 to 100 of about 2,877,467 (378)
Risk evaluation with enhanced covariance matrix [PDF]
Physica A: Statistical Mechanics and its Applications, 2007 We propose a route for the evaluation of risk based on a transformation of the covariance matrix. The approach uses a `potential' or `objective' function. This allows us to rescale data from different assets (or sources) such that each data set then has similar statistical properties in terms of their probability distributions.
Krzysztof Urbanowicz +2 more
openaire +2 more sources
Advanced Materials, EarlyView.Magnetic doping of the topological insulator Bi2Te3 with erbium adatoms induces out‐of‐plane magnetism and breaks time‐reversal symmetry, opening a Dirac gap and driving a Fermi surface transition from hexagonal to star‐of‐David geometry. Microscopy, spectroscopy, and magnetic dichroism reveal atomically controlled magnetic interactions that tailor the
Beatriz Muñiz Cano +18 more
wiley +1 more source
Estimation of a Covariance Matrix with Zeros
, 2005 We consider estimation of the covariance matrix of a multivariate random vector under the constraint that certain covariances are zero. We first present an algorithm, which we call Iterative Conditional Fitting, for computing the maximum likelihood ...
Chaudhuri, Sanjay +2 more
core +2 more sources
Recovering Linear Causal Models with Latent Variables via Cholesky Factorization of Covariance Matrix [PDF]
, 2023 Yunfeng Cai, Xu Li, Minging Sun, Ping Li
openalex +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Multivariate time series classification using kernel matrix
Electronics Letters, 2022 Multivariate time series (MTS) classification is a fundamental problem in time series mining, and the approach based on covariance matrix is an attractive way to solve the classification. In this study, it is noted that a traditional covariance matrix is
Jiancheng Sun +4 more
doaj +1 more source
Advanced Sustainable Systems, EarlyView.This article explores what drives households to adopt solar PV and battery systems in South East Queensland. Using hybrid discrete choice experiments, it reveals distinct adopter profiles and highlights cost, system size, and energy independence as key motivators.
Mohammad Alipour +3 more
wiley +1 more source
Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions [PDF]
IEEE Transactions on Signal Processing, 2015 This paper considers the problem of robustly estimating a structured covariance matrix with an elliptical underlying distribution with a known mean. In applications where the covariance matrix naturally possesses a certain structure, taking the prior ...
Ying Sun, P. Babu, D. Palomar
semanticscholar +1 more source
Using Bayesian Optimization to Increase the Efficiency of III‐V Multijunction Solar Cells
Advanced Theory and Simulations, EarlyView.Technology Computer Aided Design (TCAD) modeling is crucial for designing complex optoelectronic devices like III‐V multijunction solar cells. Bayesian optimization is proposed as a robust method to address challenges in optimizing costly black‐box TCAD solvers.
Pablo F. Palacios, Carlos Algora
wiley +1 more source
Advanced Science, EarlyView.Glycosylation, specifically hypersialylation, is identified as a critical factor in human intervertebral disc (IVD) degeneration—a major cause of low back pain. This study demonstrates that inhibiting sialylation reduces inflammation and oxidative stress in IVD tissues, suggesting new therapeutic possibilities.
Kieran Joyce +8 more
wiley +1 more source