Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained ...

Abstract: In this article, an evolution-guided adaptive dynamic programming (EGADP) algorithm is developed to address the optimal regulation problems for the nonlinear systems. In the traditional ...

OpenAI and Google DeepMind demonstrated that their foundation models could outperform human coders — and win — showing that large language models (LLMs) can solve complex, previously unsolved ...

This work extends our prior work on the distributed nonlinear model predictive control (NMPC) for navigating a robot fleet following a certain flocking behavior in unknown obstructed environments with ...

Computer science involves much more than writing code. It blends technical knowledge —like programming, algorithms and data systems — with soft skills, such as communication and problem-solving.

Abstract: DC-DC converters are extensively deployed across a range of new energy applications. However, traditional control methods that rely on accurate state space models encounter limitations in dc ...

Genomics is playing an important role in transforming healthcare. Genetic data, however, is being produced at a rate that far outpaces Moore’s Law. Many efforts have been made to accelerate genomics ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. There is a need for design strategies that can support rapid and widespread deployment ...

The old Babylonian algorithm, a remarkable mathematical artifact from ancient Mesopotamia (around 1800–1600 BC), has long been a subject of fascination to scholars. This ancient algorithm not only ...