Results 191 to 200 of about 10,511 (262)

Enhancing Prediction by Incorporating Entropy Loss in Volatility Forecasting. [PDF]

Entropy (Basel)
Urniezius R, Petrauskas R, Vaitkus V, Karimov J, Brazauskas K, Repsyte J, Kacerauskiene E, Harms T, Dargiene J, Ezerskis D.   +9 more
europepmc   +1 more source

Identifying Nonlinearities in Spatial Autoregressive Models

, 2009
Debarsy, Nicolas, Verardi, Vincenzo
openaire   +1 more source

Transfer Learning for Transformer‐Based Drought Forecasting Across Diverse Precipitation Products in India

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Effective drought management is critical for agriculture‐based economies like India. This study examines whether a transformer‐based architecture can function as a robust pre‐trained backbone for operational drought forecasting across India. We utilized a pre‐trained transformer model, which was trained on the Indian Monsoon Data Assimilation ...
Ashish Pathania, Vivek Gupta
wiley   +1 more source

Hybrid modeling and forecasting of COVID-19: integrating SEAIQHRD and GPR for improved predictions. [PDF]

BMC Infect Dis
Rao MA, Jaradat EK, Devi MP, Dhandapani PB, Nalule RM, Al-Hmoud M.   +5 more
europepmc   +1 more source

Pro‐Market Economic Reforms and Resource Curse: Do Initial Conditions Matter?

Economics of Transition and Institutional Change, Volume 34, Issue 2, Page 219-242, April 2026.
ABSTRACT The quality of economic institutions plays a crucial role in enhancing a country's economic performance, leading international organisations to recommend pro‐market institutional reforms as a strategy to support economic development. This paper investigates how the natural resource curse affects pro‐market reforms, analysing a sample of 90 ...
Isaac Amedanou, Kwamivi Mawuli Gomado
wiley   +1 more source

Aligning statistical models with inference goals in the neuroscience of language: A dual-dependency taxonomy. [PDF]

Imaging Neurosci (Camb)
Bouton S, Chambon V, Golestani N, Formisano E, Proix T, Giraud AL.   +5 more
europepmc   +1 more source

Exploring Transfer Learning's Impact on the Explainability of Deep Learning Models for Wastewater Treatment Plants' Biogas Production

Expert Systems, Volume 43, Issue 4, April 2026.
ABSTRACT The growing reliance on fossil fuels for energy generation has raised concerns about their significant contribution to global warming and the associated risks of supply instability. Anaerobic Digestion (AD) within Wastewater Treatment Plants (WWTPs) offers a renewable alternative by producing biogas, while effective operational optimisation ...
Pedro Oliveira, Afonso Bessa, João Pereira, Sérgio Silva, Maria Salomé Duarte, Dalila Durães, Paulo Novais   +6 more
wiley   +1 more source

A Quasi-Monte Carlo Method Based on Neural Autoregressive Flow. [PDF]

Entropy (Basel)
Wei Y, Xi W.
europepmc   +1 more source

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications

Journal of Economic Surveys, Volume 40, Issue 2, Page 915-953, April 2026.
ABSTRACT Probabilistic machine learning models offer a distinct advantage over traditional deterministic approaches by quantifying both epistemic uncertainty (stemming from limited data or model knowledge) and aleatoric uncertainty (due to inherent randomness in the data), along with full distributional forecasts.
Sivert Eggen, Tord Johan Espe, Kristoffer Grude, Morten Risstad, Rickard Sandberg   +4 more
wiley   +1 more source

Dynamic Modeling with Intensive Longitudinal Data: One-Step and Two-Step DSEM Approaches. [PDF]

Struct Equ Modeling
Wang L, Fang Y, Bergeman CS.
europepmc   +1 more source