This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...
A machine learning project to predict loan default risk using financial and credit history data. Built as part of a team capstone project in master degree at Deakin University. BayesCOOP is a scalable ...
TL;DR: Valve's Steam Machine, a PC-console hybrid launching next year, targets 4K 60FPS but can output 4K at 120Hz via HDMI 2.0 with reduced color quality and no HDR. Equipped with DisplayPort 1.4, it ...
Imagine a town with two widget merchants. Customers prefer cheaper widgets, so the merchants must compete to set the lowest price. Unhappy with their meager profits, they meet one night in a ...
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Discovered in 1985, the HI field lies about 50 kilometers offshore in 100 meters of water and holds an estimated 285 million barrels of oil equivalent in recoverable resources. The development is ...
Abstract: Heart attacks are a prominent source of morbidity and mortality globally, demanding the development of precise and efficient predictive models for early identification and risk ...
Shell is preparing to start production of liquefied natural gas from the second train at its installation in British Columbia, set to boost the total output from the facility by 6.5 million tons. The ...
Abstract: In this paper, we showcase the efficiency of machine learning (ML) algorithms to predict fractal antenna output response metrics. Radial basis function and least squared regression ...
Endeavour Silver is at a transformational point, with Terronera and Kolpa set to double output and lower costs, elevating it to intermediate producer status. Silver's multi-year supply deficit, ...
A new USDA directive intends to bolster the efficiency of U.S. energy production in national forests but timber and environmental groups are uncertain of its practical effects. The policy means to ...
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