Search Results for author:
Found 4 papers, 0 papers with code
Physics-based parameterized neural ordinary differential equations: prediction of laser ignition in a rocket combustor
In this work, we present a novel physics-based data-driven framework for reduced-order modeling of laser ignition in a model rocket combustor based on parameterized neural ordinary differential equations (PNODE).
Feature Engineering and Classification Models for Partial Discharge in Power Transformers
These features represent the entire signal and not just a single phase, so the feature set has a fixed size and is easily comprehensible.
Robots of the Lost Arc: Self-Supervised Learning to Dynamically Manipulate Fixed-Endpoint Cables
The framework finds a 3D apex point for the robot arm, which, together with a task-specific trajectory function, defines an arcing motion that dynamically manipulates the cable to perform tasks with varying obstacle and target locations.
Intersection complexes and unramified $L$-factors
Such relationships were previously established in Braverman-Finkelberg-Gaitsgory-Mirkovic for the affine closure of the quotient of a reductive group by the unipotent radical of a parabolic, and in Bouthier-Ngo-Sakellaridis for toric varieties and L-monoids.
Representation Theory Algebraic Geometry Number Theory
