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Found 7 papers, 4 papers with code
Multi-Modal Conformal Prediction Regions with Simple Structures by Optimizing Convex Shape Templates
While prior work has gone into creating score functions that produce multi-model prediction regions, such regions are generally too complex for use in downstream planning and control problems.
Repairing Learning-Enabled Controllers While Preserving What Works
However, existing repair techniques do not preserve previously correct behaviors.
Distributionally Robust Statistical Verification with Imprecise Neural Networks
A particularly challenging problem in AI safety is providing guarantees on the behavior of high-dimensional autonomous systems.
Causal Repair of Learning-enabled Cyber-physical Systems
However, given the high diversity and complexity of LECs, it is challenging to encode domain knowledge (e. g., the CPS dynamics) in a scalable actual causality model that could generate useful repair suggestions.
Conformal Prediction Regions for Time Series using Linear Complementarity Programming
In fact, to obtain prediction regions over $T$ time steps with confidence $1-\delta$, {previous works require that each individual prediction region is valid} with confidence $1-\delta/T$.
Risk Verification of Stochastic Systems with Neural Network Controllers
Motivated by the fragility of neural network (NN) controllers in safety-critical applications, we present a data-driven framework for verifying the risk of stochastic dynamical systems with NN controllers.
Confidence Composition for Monitors of Verification Assumptions
To predict safety violations in a verified system, we propose a three-step confidence composition (CoCo) framework for monitoring verification assumptions.
