A horizon-agnostic neural operator paired with a boundary control barrier function creates a real-time safety filter that raises safe trajectory rates by up to 22% on fluid manipulation tasks in simulation.
Physics-informed neural operator for learning partial differential equations
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
A unified space-time fractional PDE characterizes long-term risk probabilities in systems with asymmetric jumps and memory, solved via physics-informed learning for accurate and generalizable predictions.
citing papers explorer
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Online Safety Filter for Deformable Object Manipulation with Horizon Agnostic Neural Operators
A horizon-agnostic neural operator paired with a boundary control barrier function creates a real-time safety filter that raises safe trajectory rates by up to 22% on fluid manipulation tasks in simulation.
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Fractional Risk Analysis of Stochastic Systems with Jumps and Memory
A unified space-time fractional PDE characterizes long-term risk probabilities in systems with asymmetric jumps and memory, solved via physics-informed learning for accurate and generalizable predictions.