Results 171 to 180 of about 11,306 (311)
Realtime nowcasting with a Bayesian mixed frequency model with stochastic volatility. [PDF]
Carriero A, Clark TE, Marcellino M.
europepmc +1 more source
Discriminating between GARCH and stochastic volatility via nonnested hypotheses testing
Philip Messow
openalex +1 more source
A Flexible and Energy‐Efficient Compute‐in‐Memory Accelerator for Kolmogorov–Arnold Networks
This article presents KA‐CIM, a compute‐in‐memory accelerator for Kolmogorov–Arnold Networks (KANs). It enables flexible and efficient computation of arbitrary nonlinear functions through cross‐layer co‐optimization from algorithm to device. KA‐CIM surpasses CPU, ASIC, VMM‐CIM, and prior KAN accelerators by 1–3 orders of magnitude in energy‐delay ...
Chirag Sudarshan +6 more
wiley +1 more source
PRACTICAL INVESTMENT STRATEGIES UNDER A MULTI-SCALE HESTON'S STOCHASTIC VOLATILITY MODEL [PDF]
Jai Heui Kim, Sotheara Veng
openalex +1 more source
Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera +2 more
wiley +1 more source
Methods for Setting Device Specifications for Analog In‐Memory Computing Inference
Non‐volatile memories (NVMs) are being developed for analog in‐memory computing for energy‐efficient, high‐speed deep learning inference. As technology is moving to industry adoption, a method to define required NVM specifications is critical for improving performance and reducing manufacturing cost.
Zhenyu Wu +3 more
wiley +1 more source
Baldovin-Stella stochastic volatility process and Wiener process mixtures
Pier Paolo Peirano, Damien Challet
openalex +2 more sources
Artificial intelligence (AI) is reshaping autonomous mobile robot navigation beyond classical pipelines. This review analyzes how AI techniques are integrated into core navigation tasks, including path planning and control, localization and mapping, perception, and context‐aware decision‐making. Learning‐based, probabilistic, and soft‐computing methods
Giovanna Guaragnella +5 more
wiley +1 more source
Pricing via Quantization in Stochastic Volatility Models
Giorgia Callegaro +2 more
openalex +1 more source

