Results 161 to 170 of about 22,553 (296)
Artificial Intelligence for Fluorite Ferroelectric Materials: From Discovery to Optimization
Advanced Electronic Materials, EarlyView.Artificial intelligence accelerates the discovery and optimization of HfO2‐based fluorite ferroelectrics by linking synthesis, structure, properties, and device performance. Machine learning, deep‐learning analysis, and AI‐driven atomistic modeling enable predictive design, dopant screening, and closed‐loop optimization toward next‐generation ...
Faizan Ali +3 more
wiley +1 more source
High order discretization schemes for stochastic volatility models [PDF]
In usual stochastic volatility models, the process driving the volatility of the asset price evolves according to an autonomous one-dimensional stochastic differential equation. We assume that the coefficients of this equation are smooth.
Mohamed Sbai, Benjamin Jourdain
core
Multivariate stochastic volatility modeling of neural data. [PDF]
Elife, 2019 Phan TD +3 more
europepmc +1 more source
Linear and Programmable Long‐Term Plasticity in PECVD Amorphous SiC Memristors
Advanced Electronic Materials, EarlyView.Stoichiometry‐engineered PECVD amorphous SiC memristors exhibit highly linear and programmable long‐term synaptic plasticity with a nonlinearity as low as 0.08. By controlling the local bonding environment, stable multilevel conductance updates are achieved, enabling robust neural‐network classification on MNIST and CIFAR‐10 and highlighting amorphous ...
Qin Liu +6 more
wiley +1 more source
Advanced Electronic Materials, EarlyView.X‐ray irradiation suppresses inhibitory plasticity in SnO‐based volatile memristors, reducing nonlinearity and variability while improving neuromorphic learning accuracy. Despite a reduced dynamic range, irradiated devices achieve more stable and linear synaptic updates, leading to enhanced CNN performance.
Aiden Graham +12 more
wiley +1 more source
"Block Sampler and Posterior Mode Estimation for Asymmetric Stochastic Volatility Models" [PDF]
This article introduces a new efficient simulation smoother and disturbance smoother for asymmetric stochastic volatility models where there exists a correlation between today's return and tomorrow's volatility.
Toshiaki Watanabe, Yasuhiro Omori
core
Advanced Electronic Materials, EarlyView.Pulse‐protocol optimization in an Au/MoO3/TiO2/FTO bilayer memristor enables linear analog synaptic conductance modulation along with digital resistive switching for memory. Controlled filament evolution produces stable learning‐forgetting characteristics with low nonlinearity, resulting in significantly enhanced neural network inference accuracy for ...
Girish Chandrashekar +2 more
wiley +1 more source
Pricing and Hedging Options in Incomplete Markets: Idiosyncratic Risk, Systematic Risk and Stochastic Volatility [PDF]
Starting from the European option valuation framework of Chauveau & Gatfaoui (2002), we establish the link with stochastic volatility models. And, we propose both a new vision and a general framework for valuing European options in the light of ...
Gatfaoui Hayette, Chauveau Thierry
core
Low Participation and Risk Reduction Potential of Supplemental Crop Insurance in the United States
Applied Economic Perspectives and Policy, EarlyView.ABSTRACT Federally subsidized crop insurance is a cornerstone of U.S. farm risk management, yet policies with the greatest share of participation only trigger indemnities after losses exceed 15%. Supplemental insurance was introduced to cover part of this deductible, but participation remains largely unchanged.
Francis Tsiboe +2 more
wiley +1 more source
Forecasting Value-at-Risk Using Block Structure Multivariate Stochastic Volatility Models [PDF]
Most multivariate variance or volatility models suffer from a common problem, the “curse of dimensionality”. For this reason, most are fitted under strong parametric restrictions that reduce the interpretation and flexibility of the models. Recently, the
Michael McAleer +2 more
core +2 more sources