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5 papers

math.AP2026

Neural Network Approximation of Solutions to Fractional Parabolic Partial Differential Equations

Jae-Hwan Choi, Hyojae Lim, Jinsol Seo +2

The paper develops a dimension‑efficient neural network approximation theory for solutions of fractional parabolic PDEs, introducing anisotropic spectral Barron spaces and proving…

cs.LO2026

Lean-GAP: A Dataset of Formalized Graduate Algebra Problems

Seewoo Lee, Byung-Hak Hwang, Hyojae Lim +10

We present Lean-GAP (Lean-Graduate Agebra Problems), 430 formalized graduate-level algebra problems from the textbook Abstract Algebra by Dummit and Foote. We develop a scalable pi…

math.FA2025

New Tight Wavelet Frame Constructions Sharing Responsibility

Youngmi Hur, Hyojae Lim

Tight wavelet frames (TWFs) in \(L^2(\mathbb{R}^n)\) are versatile, and are practically useful due to their perfect reconstruction property. Nevertheless, existing TWF construction…

cs.LG2025

Provable wavelet-based neural approximation

Youngmi Hur, Hyojae Lim, Mikyoung Lim

In this paper, we develop a wavelet-based theoretical framework for analyzing the universal approximation capabilities of neural networks over a wide range of activation functions.…

cs.LO2025

Simplifying Formal Proof-Generating Models with ChatGPT and Basic Searching Techniques

Sangjun Han, Taeil Hur, Youngmi Hur +3

The challenge of formal proof generation has a rich history, but with modern techniques, we may finally be at the stage of making actual progress in real-life mathematical problems…