Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...
Cristani, C. and Tessera, D. (2026) A Foundational Protocol for Reproducible Visualization in Multivariate Quantum Data. Open Access Library Journal, 13, 1-13. doi: 10.4236/oalib.1114704 .
These are self-study notes for the course Nonequilibrium Field Theories and Stochastic Dynamics (Prof. Erwin Frey, LMU Munich, Summer Semester 2025). Prof. Erwin Frey prefers chalkboard lectures. To ...
Abstract: This paper presents Post-Decision Proximal Policy Optimization (PDPPO), a novel variation of the leading deep reinforcement learning method, Proximal Policy Optimization (PPO). The PDPPO ...
For obvious reasons, it would be useful to predict when an earthquake is going to occur. It has long been suspected that large quakes in the Himalayas follow a fairly predictable cycle, but nature, as ...
A new Wharton study explains why stock returns aren’t random. Correlation neglect causes market overreaction, momentum, and reversals investors consistently misprice.
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Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...
Learn what flow and stock variables mean in simple terms. Understand how income, wealth, GDP, and debt connect through time and why this matters in economics and everyday life.
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