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Deep heteroscedastic regression involves jointly optimizing the mean and covariance of the predicted distribution using the negative log-likelihood. However, recent works show that this may result in sub-optimal convergence due to the challenges associated ...
With the increasing complexity of engineered systems, digital twins (DTs) have been widely used to support integrated modeling, simulation, and decision-making of the system of systems (SoS). However, when integrating DTs of each constituent system, it is ...
Background Subjective cognitive decline (SCD) is the subjective perception of a decline in memory and/or other cognitive functions in the absence of objective evidence. Some SCD individuals however may suffer from very early stages of neurodegenerative dis ...
Autism is a wide-spectrum disorder with early childhood onset, affecting general cognitive capabilities and, in particular, complex information processing. Although interesting directions of research start to appear, the precise causes of the disorder and ...
Cognitive deficits in individuals at risk of psychosis represent a significant challenge for research, as current strategies for symptomatic treatment are often ineffective. Recent studies showed that atypical cognitive development predicts the occurrence ...
In time-sensitive networks, bounds on worst-case delays are typically obtained by using network calculus and assuming that flows are constrained by bit-level arrival curves. However, in IEEE TSN or IETF DetNet, source flows are constrained on the number of ...
A series of three shear panels with transverse reinforcing ratios ranging from 0.23 to 0.68% were tested to failure under reversed cyclic loading. All of the tests showed a reduction in strength of at least 20% with respect to predictions from reliable mon ...