IEEE

Distribution-Free Probability Density Forecast Through Deep Neural Networks

Abstract: Probability density forecast offers the whole distributions of forecasting targets, which brings greater flexibility and practicability than the other probabilistic forecast models such as ...
C&EN

From the Electron Density Gradient to the Quantitative Reactivity Indicators: Local Softness and the Fukui Function

You are free to share (copy and redistribute) this article in any medium or format within the parameters below: Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must ...
IEEE

Deep-Based Conditional Probability Density Function Forecasting of Residential Loads

Abstract: This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can ...
Investopedia

Understanding Prior Probability in Bayesian Statistics

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...