Tag: uncertainty quantification

A new review of 29 recent studies finds that no deep learning intrusion detection system has been evaluated jointly for ...

A new study of Swiss catchments shows that deterministic LSTMs underestimate 97 percent of the most extreme floods, while probabilistic ...

Researchers outline a comprehensive blueprint for building trustworthy foundation models that emulate expensive physics simulations on exascale supercomputers.

Researchers have built a Bayesian liquid neural network that scores posture quality while quantifying its own uncertainty and abstaining from ...

A new Frontiers in Remote Sensing collection showcases polarimetric cloud imaging, cloud tomography, event-based lightning sensors, adaptive pointing strategies, and ...

Oxford researchers argue that the common practice of reducing expert annotations to single binary masks introduces a hidden source of ...

A detailed performance assessment by Swiss waste management agency Nagra demonstrates that the planned deep geological repository at Haberstal maintains ...

Researchers have built a 10.97-million-parameter neural network that classifies brain tumors on MRI with 99.2 percent accuracy while quantifying its ...

Researchers have developed a conformal calibration method that borrows statistical strength across sparse group-horizon cells to fix hidden coverage gaps ...

A new framework called FLARE combines nonlinear machine learning flexibility with closed-form uncertainty estimates, statistical tests, and patient-level interaction analysis ...