Artificial Intelligence (AI) has made impressive progress in recent year...
Fatigue strength estimation is a costly manual material characterization...
We interpret solving the multi-vehicle routing problem as a team Markov ...
Uncertainty estimation bears the potential to make deep learning (DL) sy...
The majority of popular graph kernels is based on the concept of Haussle...
We introduce the notion of weak convexity in metric spaces, a generaliza...
The Weisfeiler-Lehman graph kernels are among the most prevalent graph
k...
Quantification of uncertainty is one of the most promising approaches to...
Quantification of uncertainty is one of the most promising approaches to...
Traditional neural networks represent everything as a vector, and are ab...
We investigate some algorithmic properties of closed set and half-space
...
We propose an efficient protocol for decentralized training of deep neur...
Quantum computing for machine learning attracts increasing attention and...
Echo state networks are simple recurrent neural networks that are easy t...