Ronald Katende
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226
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Algorithms×1Complexity×1Combinatorics×1Numerical Analysis×1Comp. Eng.×1ML×1
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2026
Physics-Informed Residuals for Adaptive Mesh Refinement in Finite-Difference PDE Solvers
The paper proposes using a Physics-Informed Neural Network (PINN) residual as an efficient, physics-guided indicator to guide adaptive mesh refinement (AMR) for classical finite-difference PDE solvers, significantly reducing required degrees of freedom.
Contextual Fraction on Permutation Gain Graphs: Exact Algorithms, Query Lower Bounds, and Dynamic Maintenance
This paper identifies a tractability island inside the contextual-fraction problem by collapsing it to a fixed-point calculation for a specific class of permutation-transport models.
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cs.DScs.CCmath.COTheoreticalRecentJul 17, 2026
Contextual Fraction on Permutation Gain Graphs: Exact Algorithms, Query Lower Bounds, and Dynamic Maintenance
This paper identifies a tractability island inside the contextual-fraction problem by collapsing it to a fixed-point calculation for a specific class of permutation-transport models.
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math.NAcs.CEcs.LGRecent