Risk‐aware safe reinforcement learning for control of stochastic linear systems
Asian Journal of Control, EarlyView.Abstract This paper presents a risk‐aware safe reinforcement learning (RL) control design for stochastic discrete‐time linear systems. Rather than using a safety certifier to myopically intervene with the RL controller, a risk‐informed safe controller is also learned besides the RL controller, and the RL and safe controllers are combined together ...
Babak Esmaeili +2 more
wiley +1 more source
Penggunaan metode Heteroscedasticity Consistent Covariance Matrix Estimator (HCCME) untuk mengatasi Heteroskedastisitas pada regresi linier [PDF]
, 2018 Solichin Muchorobin
openalex
Quasi-entropy by log-determinant covariance matrix and application to liquid crystals
, 2020 Jie Xu
openalex +1 more source
Nonparametric eigenvalue-regularized precision or covariance matrix estimator
, 2016 Clifford Lam
semanticscholar +1 more source
Regional Shopping Objectives in British Grocery Retail Transactions Using Segmented Topic Models
Applied Stochastic Models in Business and Industry, EarlyView.ABSTRACT Understanding the customer behaviours behind transactional data has high commercial value in the grocery retail industry. Customers generate millions of transactions every day, choosing and buying products to satisfy specific shopping needs.
Mariflor Vega Carrasco +4 more
wiley +1 more source
On the Significance of the Quantum Mechanical Covariance Matrix. [PDF]
Entropy (Basel), 2018 Carmi A, Cohen E.
europepmc +1 more source
Confirmation of a Non‐Transiting Planet in the Habitable Zone of the Nearby M Dwarf L 98‐59
Astronomische Nachrichten, EarlyView.ABSTRACT Only 40 exoplanetary systems with five or more planets are currently known. These systems are crucial for our understanding of planet formation and planet‐planet interaction. The M dwarf L 98‐59 has previously been found to show evidence of five planets, three of which are transiting.
Paul I. Schwarz +2 more
wiley +1 more source
The classical multivariate regression model with singular covariance matrix
, 1971 D. Neeleman
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Generative Deep Learning for Advanced Battery Materials
Batteries &Supercaps, EarlyView.This review explores the role of generative deep learning (DL) in battery materials analysis and highlights the fundamental principles of generative DL and its applications in designing battery materials. The importance of using multimodal data is underscored to effectively address the challenges faced during the development of battery materials across
Deepalaxmi Rajagopal +3 more
wiley +1 more source