This toolkit is designed to be used for super simple neural network use cases. It is not designed for any advanced AI applications but should be used as a starting point, evaluation or proof of ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and robust ...

Machine learning is the ability of a machine to improve its performance based on previous results. Machine learning methods enable computers to learn without being explicitly programmed and have ...

Abstract: Robust multiobjective optimization problems (RMOPs) widely exist in real-world applications, which introduce a variety of uncertainty in optimization models. While some evolutionary ...

Abstract: Path planning is a crucial component for robotics and autonomous systems, which facilitate navigation through dynamic and uncertain environments while avoiding obstacles. This review paper ...