Abstract: Probabilistic forecasting of multivariate time series is essential for various downstream tasks. Most existing approaches rely on the sequences being uniformly spaced and aligned across all ...

Data operationalization, complemented by the pragmatic deployment of AI use cases with said data, is, at its core, a move ...

The proliferation of nuclear power in space got a little more real Tuesday with the launch of a small satellite developed by ...

PROB adapts the Deformable DETR model by adding the proposed 'probabilistic objectness' head. In training, we alternate between distribution estimation (top right) and objectness likelihood ...

Abstract: In this study, train operations were modeled by Bayesian networks (BN), to use the probability essence of the BN to quantify their uncertainty (e.g., the epistemic and aleatoric uncertainty ...

I was working professionally when the cloud became a thing. From that vantage I saw initial adoption: the excitement, the flexibility, the sense that everything was going to move faster. This led to ...

Students of many scientific disciplines often find difficulties in defining concepts, making and proving claims, etc., that affect their education negatively. If they do not enhance their critical, ...