ACoFi adaptively tunes the switching threshold of learned safety filters using conformal inference on the range of predicted safety values, asymptotically bounding the rate of incorrect safety assessments by a user parameter and reducing violations versus fixed thresholds in simulations.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 2verdicts
UNVERDICTED 2roles
background 1polarities
background 1representative citing papers
A survey organizing AI methods for inverse PDE problems into inverse problems, inverse design, and control categories, covering applications and future challenges like physics-informed models and uncertainty quantification.
citing papers explorer
-
Safe Control using Learned Safety Filters and Adaptive Conformal Inference
ACoFi adaptively tunes the switching threshold of learned safety filters using conformal inference on the range of predicted safety values, asymptotically bounding the rate of incorrect safety assessments by a user parameter and reducing violations versus fixed thresholds in simulations.
-
Harnessing AI for Inverse Partial Differential Equation Problems: Past, Present, and Prospects
A survey organizing AI methods for inverse PDE problems into inverse problems, inverse design, and control categories, covering applications and future challenges like physics-informed models and uncertainty quantification.