When you're trying to get the best performance out of Python, most developers immediately jump to complex algorithmic fixes, using C extensions, or obsessively running profiling tools. However, one of ...

Concr CEO Irina Babina and CTO Matthew Griffiths unpack how Bayesian foundation models can excel at uncertainty management to ...

Abstract: Movable antennas (MAs) have garnered significant attention in communication systems due to their flexible geometry arrays, which introduce a new degree of freedom. Numerous studies ...

This project uses Bayesian Optimization to find the optimal hyperparameters for a fully-connected feed-forward neural network used to estimate the heating load on a building given eight different i… ...

Abstract: Mobility management in cellular networks faces increasing complexity due to network densification and heterogeneous user mobility characteristics. Traditional handover (HO) mechanisms, which ...

In his project, we proposed a new acquisition function for kriging-based reliability analysis, namely expected uncertainty reduction (EUR), that serves as a meta-criterion to select the best sample… ...