Results 121 to 130 of about 35,395 (320)
Business Strategy and the Environment, EarlyView.ABSTRACT The pressure on corporations to contribute to sustainable development is increasing. It is widely recognised that the sustainable development goals and deadlines cannot be achieved without the support of incumbent firms. Business model innovation (BMI) is identified as a means for businesses to contribute to sustainable development.
Mercy Masaeli +3 more
wiley +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Chemistry – A European Journal, EarlyView.ABSTRACT Machine learning (ML) models are increasingly used in quantum chemistry, but their reliability hinges on uncertainty quantification (UQ). In this study, we compare two prominent UQ paradigms—deep evidential regression (DER) and deep ensembles—on the QM9 and WS22 datasets, with a specific emphasis on the role of post hoc calibration.
Bidhan Chandra Garain +3 more
wiley +1 more source
MathematicsThe development of artificial intelligence (AI) game agents that use deep reinforcement learning (DRL) algorithms to process visual information for decision-making has emerged as a key research focus in both academia and industry.
Zihao Cui +4 more
doaj +1 more source
The Canadian Journal of Chemical Engineering, EarlyView.Abstract Identification of firefighting strategies (i.e., which endangered units to suppress or cool first) in chemical and process plants falls under the domain of multi‐objective decision‐making (MODM), where not only the safety and integrity of the affected process plant but also the safety of on‐site and off‐site vulnerable targets matter.
Sina Khakzad, Nima Khakzad
wiley +1 more source
Restricted Tweedie stochastic block models
Canadian Journal of Statistics, EarlyView.Abstract The stochastic block model (SBM) is a widely used framework for community detection in networks, where the network structure is typically represented by an adjacency matrix. However, conventional SBMs are not directly applicable to an adjacency matrix that consists of nonnegative zero‐inflated continuous edge weights.
Jie Jian, Mu Zhu, Peijun Sang
wiley +1 more source
Value-Function Approximations for Partially Observable Markov Decision Processes
Journal of Artificial Intelligence Research, 2000 Partially observable Markov decision processes (POMDPs) provide an elegant mathematical framework for modeling complex decision and planning problems in stochastic domains in which states of the system are observable only indirectly, via a set of imperfect or noisy observations. The modeling advantage of POMDPs, however, comes at a price
openaire +4 more sources
Optimal dividends for a NatCat insurer in the presence of a climate tipping point
Canadian Journal of Statistics, EarlyView.Abstract We study optimal dividend strategies for an insurance company facing natural catastrophe claims, anticipating the arrival of a climate tipping point after which the claim intensity and/or the claim size distribution of the underlying risks deteriorates irreversibly.
Hansjörg Albrecher +2 more
wiley +1 more source
Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions
Canadian Journal of Statistics, EarlyView.Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni +2 more
wiley +1 more source
A Markov approach to credit rating migration conditional on economic states
Canadian Journal of Statistics, EarlyView.Abstract We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time‐homogeneous Markov chain. While the rating process itself possesses the Markov property only under restrictive conditions, methods ...
Michael Kalkbrener, Natalie Packham
wiley +1 more source
Bayesian clustering of multivariate extremes
Canadian Journal of Statistics, EarlyView.Abstract The asymptotic dependence structure between multivariate extreme values is fully characterized by their projections on the unit simplex. Under mild conditions, the only constraint on the resulting distributions is that their marginal means must be equal, which results in a nonparametric model that can be difficult to use in applications ...
Sonia Alouini, Anthony C. Davison
wiley +1 more source