works on

From the 1 of 6 linked papers with an AI index.

collaborators

6 papers

math.NA2026

Uniform Approximation of Functions with Asymmetric Growth and Decay by Deep Weighted Polynomials

Kingsley Yeon, Steven B. Damelin

The paper proposes a class of weighted deep (composite) polynomials that can uniformly approximate functions which grow on one side of the real line and decay on the other, and dem…

quant-ph2026

Typical-Case Gate Approximation and Arithmetic Obstructions in Quaternionic Single-Qubit Compilation

Kingsley Yeon, Steven B. Damelin, Alec Greene

Fault-tolerant quantum computation requires compiling arbitrary one-qubit unitaries into short words over a fixed gate library. For arithmetic libraries such as the Lubotzky-…

q-bio.QM2026

Protein Thoughts: Interpretable Reasoning with Tree of Thoughts and Embedding-Space Flow Matching for Protein-Protein Interaction Discovery

Kingsley Yeon, Xuefeng Liu, Promit Ghosal

Protein-protein interactions (PPIs) govern nearly all cellular processes, yet computational methods for identifying binding partners typically produce ranked predictions without me…

math.NA2025

Exponential Convergence of Deep Composite Polynomial Approximation for Cusp-Type Functions

Kingsley Yeon, Steven B. Damelin, Michael Werman

We investigate deep composite polynomial approximations of continuous but non-differentiable functions with algebraic cusp singularities. The functions in focus consist of finitely…

math.NA2025

Beyond Low Rank: Fast Low-Rank + Diagonal Decomposition with a Spectral Approach

Kingsley Yeon, Mihai Anitescu

Low-rank plus diagonal (LRPD) decompositions provide a powerful structural model for large covariance matrices, simultaneously capturing global shared factors and localized correct…

math.NA2025

BOLT: Block-Orthonormal Lanczos for Trace estimation of matrix functions

Kingsley Yeon, Promit Ghosal, Mihai Anitescu

Efficient matrix trace estimation is essential for scalable computation of log-determinants, matrix norms, and distributional divergences. In many large-scale applications, the mat…