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Code for the paper "Rational neural networks", NeurIPS 2020
Codes for the paper 'Rational Neural Networks for Approximating Jump Discontinuities of Graph Convolution Operator' ICDM 18
This directory contains lecture notes for an undergraduate numerical analysis course offered in Spring 2018, at UT Austin.
Neural network architecture with learnable fractional power bases
Official code repo for STAI-X 2026 paper "Transformer as Provable Approximators of Sparse Principal Component Analysis".
From the Weierstrass M-test to the RBF kernel: uniform convergence with explicit error bounds, applied to kernel methods and Gaussian blur
Numerical study of convergence rates for approximating transport maps
A numerical methods project exploring different approaches to computing trigonometric functions. Combining modern C++, Python, and LaTeX to investigate approximation algorithms through reproducible numerical experiments.
Description: A straightedge-and-compass constructible cubic error cascade for approximate angle trisection.
Preliminary numerical experiments for some greedy algorithms.
Proof 7: Why the Cantor function (Devil's Staircase) is structurally hard for ReLU networks. All theorems verified.
Reproducible code, data and figures for the paper "Optimal selection of the preserved exponential in Szász–Mirakyan operators: a leading-term criterion validated at finite n" (submitted to DRNA).
Preprint and reproducibility materials for sharp closure thresholds for two-hidden-layer ReLU networks.
A port of Chebfun from MATLAB to GNU Octave.
Rigorous analysis of the Amundson sequence G(n) = n^(n+1)/(n+1)^n and the constant A_G: Hausdorff moment representation, compound-Poisson/Levy form, fibre lattices, and endpoint Christoffel asymptotics (Theorem C0).
Bernstein's constant to ten rigorously certified digits: beta = 0.2801694990, proved in interval arithmetic (Arb) where the 1985 Varga-Carpenter rigorous enclosure gives five. OEIS A073001. Every number re-derivable from the shipped data in exact arithmetic.
Certified minimax approximation of the logistic-normal integral
Volume VII of Learning Real Analysis: Numerical analysis and approximation theory.
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