Are you passionate about developing AI-based and quantum-inspired solutions for the next generation of sustainable energy systems? We are now looking for a fully funded Doctoral Researcher to work on ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

Abstract: WSNs have demonstrated to play a key role in many applications ranging from environmental monitoring to military surveillance. The problem of efficient routing however is challenging due to ...

Abstract: Urban traffic simulation is useful in many ways to understand, manage, and predict the growing complexities of traffic dynamics within a city. Traditional simulation models often struggle to ...

Is this real life? Is this just fantasy? A growing number of scientists are suggesting that the idea that we are all living in a simulation may not be completely far-fetched. Simulation theory is the ...

The success of a molecular dynamics simulation depends on the accuracy of the force field used to define the atomic interactions. It is challenging to train both classical and modern machine-learning ...