Results 61 to 70 of about 20,255,155 (246)

DeepONet-Inspired Architecture for Efficient Financial Time Series Prediction

Mathematics
Financial time series prediction is a fundamental problem in investment and risk management. Deep learning models, such as multilayer perceptrons, Convolutional Neural Networks (CNNs), and Long Short-Term Memory (LSTM), have been widely used in modeling ...
Zeeshan Ahmad, Shudi Bao, Meng Chen
doaj   +1 more source

Facial Cosmetic Therapy Use Among Patients With Systemic Sclerosis: An Australian Cohort Study

Arthritis Care &Research, EarlyView.
Objective Systemic sclerosis (SSc) is associated with numerous facial manifestations for which patients may engage in cosmetic therapies. It is unclear how patients with SSc use these therapies. This study sought to characterize patient engagement and experiences with cosmetic therapies for SSc‐related and non‐SSc–related facial changes.
Zachary Warren, Diane Apostolopoulos, Gene‐Siew Ngian, Amanda M. Saracino, Laura Ross, Nava Ferdowsi, Jennifer Walker, Cindy Hall, Kim Griggs, Susanna Proudman, Wendy Stevens, Joanne Sahhar   +11 more
wiley   +1 more source

Quantile double AR time series models for financial returns

, 2013
We develop a novel quantile double autoregressive model for modelling financial time series. This is done by specifying a generalized lambda distribution to the quantile function of the location‐scale double autoregressive model developed by Ling (2004 ...
Cai, Y., Montes-Rojas, G., Olmo, J.
core   +1 more source

A Scoping Review and Meta‐Analysis of Proportions of Central Nervous System Manifestations Reported in Patients with Sjögren's Disease

Arthritis Care &Research, Accepted Article.
Objective The objective of this scoping review was to synthesize evidence on the proportion of individuals living with Sjögren's disease who experience central nervous system (CNS) manifestations. Methods We searched MEDLINE (via PubMed) and Embase from 1980 through January 29, 2026, and the ECRI Guidelines Trust from 2020 through January 29, 2026 ...
Arun Varadhachary, Ghaith Noaiseh, Julie Frantsve‐Hawley, Frederick B. Vivino, Jennifer A. McCombe, Shamik Bhattacharyya, E. Sherwood Brown, Andrew R. Carey, Robert Fox, Thomas Grader‐Beck, Janet E. Lewis, Stephen Maitz, Steven Mandel, Astrid Rasmussen, George Sarka, R. Hal Scofield, Daniel J. Wallace, Rochelle Zak, Kristie Cox, Katherine M. Hammitt, Steven Carsons, Nancy Carteron   +21 more
wiley   +1 more source

Multiscaled cross-correlation dynamics in financial time series [PDF]

, 2009
The cross-correlation matrix between equities comprises multiple interactions between traders with varying strategies and time horizons. In this paper, we use the Maximum Overlap Discrete Wavelet Transform (MODWT) to calculate correlation matrices over ...
Crane, Martin, Ruskin, Heather J., Conlon, Thomas   +2 more
core   +2 more sources

Dynamic parameters for Brazilian financial time series

Economia Aplicada, 2002
In this study we analyse a Brazilian stock index called IBOVESPA using techniques from dynamical systems theory and stochastic processes. We discuss the Lyapunov exponent, the correlation dimension, the LempelZiv complexity, the Hurst exponent and the ...
Gerson Francisco, Cláudio Paiva, Rogerio Rosenfeld   +2 more
doaj  

AI-OPTIMIZED FUZZY CONVOLUTIONAL PREDICTION FOR FINANCIAL TIME SERIES

Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi
A deep convolutional prediction approach for financial time series is introduced in which fuzzy-cluster memberships and lagged observations are provided as inputs to a GA-tuned 1D convolutional network.
Furkan Keskin, Ozge Cagcag Yolcu, Sümeyye Polater   +2 more
doaj   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Revisiting Stability Criteria in Ball‐Milled High‐Entropy Alloys: Do Hume–Rothery and Thermodynamic Rules Equally Apply?

Advanced Engineering Materials, Volume 27, Issue 6, March 2025.
The stability criteria affecting the formation of high‐entropy alloys, particularly focusing in supersaturated solid solutions produced by mechanical alloying, are analyzed. Criteria based on Hume–Rothery rules are distinguished from those derived from thermodynamic relations. The formers are generally applicable to mechanically alloyed samples.
Javier S. Blázquez, Alejandro F. Manchón‐Gordón, Antonio Vidal‐Crespo, Rafael Caballero‐Flores, Jhon J. Ipus, Clara F. Conde   +5 more
wiley   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source