OOIR: Observatory of International Research

Papers

(The TQCC of Applied and Computational Harmonic Analysis is 6. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-12-01 to 2025-12-01.)

Article	Citations
On the limits of neural network explainability via descrambling	79
On the numerical evaluation of the prolate spheroidal wave functions of order zero	45
Convergence of sparse grid Gaussian convolution approximation for multi-dimensional periodic functions	41
Spatiotemporal analysis using Riemannian composition of diffusion operators	38
Introduction to the Special Issue on Harmonic Analysis and Machine Learning	37
A diffusion + wavelet-window method for recovery of super-resolution point-masses with application to single-molecule microscopy and beyond	36
Kadec-type theorems for sampled group orbits	34
Scale dependencies and self-similar models with wavelet scattering spectra	33
Duality for neural networks through Reproducing Kernel Banach Spaces	32
Editorial Board	30
Beurling dimension of spectra for a class of random convolutions on R<	29
Unlimited sampling beyond modulo	23
Error estimate of the u-series method for molecular dynamics simulations	21
Estimates on learning rates for multi-penalty distribution regression	21
Biorthogonal Greedy Algorithms in convex optimization	21
Dilational symmetries of decomposition and coorbit spaces	20
A note on spike localization for line spectrum estimation	20
Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning	19
On the evaluation of the eigendecomposition of the Airy integral operator	19
Computing the proximal operator of the q-th power of the ℓ1,-norm for group sparsity	18
Generalization error of random feature and kernel methods: Hypercontractivity and kernel matrix concentration	17
Sharp error estimates for target measure diffusion maps with applications to the committor problem	17
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks	16
Signal reconstruction using determinantal sampling	16
Complete interpolating sequences for the Gaussian shift-invariant space	15

Controlled learning of pointwise nonlinearities in neural-network-like architectures	14
AP-frames and stationary random processes	14
Finite alphabet phase retrieval	14
Editorial Board	14
A simple approach for quantizing neural networks	14
Irregular Gabor frames of Cauchy kernels	13
n-Best kernel approximation in reproducing kernel Hilbert spaces	12
Gaussian random field approximation via Stein's method with applications to wide random neural networks	12
A fractal uncertainty principle for the short-time Fourier transform and Gabor multipliers	12
Marcinkiewicz–Zygmund inequalities for scattered and random data on the q-sphere	12
On the number of faces and radii of cells induced by Gaussian spherical tessellations	12
Eigenmatrix for unstructured sparse recovery	12
Editorial Board	11
Data-driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application	11
On the relation between Fourier and Walsh–Rademacher spectra for random fields	11
Adaptive parameter selection for kernel ridge regression	11
An efficient spatial discretization of spans of multivariate Chebyshev polynomials	11
Stable parameterization of continuous and piecewise-linear functions	10
On the intermediate value property of spectra for a class of Moran spectral measures	10
Regularization of inverse problems by filtered diagonal frame decomposition	10
Divergence-free quasi-interpolation	9
Solving phase retrieval with random initial guess is nearly as good as by spectral initialization	9
On the accuracy of Prony's method for recovery of exponential sums with closely spaced exponents	9
An unbounded operator theory approach to lower frame and Riesz-Fischer sequences	9
Estimation under group actions: Recovering orbits from invariants	9
A sufficient condition for mobile sampling in terms of surface density	9
Frames of translates for model sets	9
Weighted variation spaces and approximation by shallow ReLU networks	8
Dimension reduction, exact recovery, and error estimates for sparse reconstruction in phase space	8
Spectral analysis of weighted Laplacians arising in data clustering	8
Lower bounds on the low-distortion embedding dimension of submanifolds of 8
A tighter generalization error bound for wide GCN based on loss landscape	8
Sparse free deconvolution under unknown noise level via eigenmatrix	8
Editorial Board	7
Constructive subsampling of finite frames with applications in optimal function recovery	7
Algebraic compressed sensing	7
Positive definite multi-kernels for scattered data interpolations	7
Generalization bounds for sparse random feature expansions	7
Laplace-Beltrami operator on the orthogonal group in ambient (Euclidean) coordinates	7
Tikhonov regularization for Gaussian empirical gain maximization in RKHS is consistent	7
Fundamental component enhancement via adaptive nonlinear activation functions	7
A unified approach to synchronization problems over subgroups of the orthogonal group	7
A one-bit, comparison-based gradient estimator	7
Synthesis-based time-scale transforms for non-stationary signals	7
Editorial Board	7
Optimal (α,d)-multi-completion of d-designs	7
The springback penalty for robust signal recovery	7
On a regularization of unsupervised domain adaptation in RKHS	6
Frames by orbits of two operators that commute	6
The G-invariant graph Laplacian part II: Diffusion maps	6

Universal Approximation Property of Fully Convolutional Neural Networks with Zero Padding	6
Solving PDEs on unknown manifolds with machine learning	6
Sparsification of the regularized magnetic Laplacian with multi-type spanning forests	6
Permutation-invariant representations with applications to graph deep learning	6
Editorial Board	6
Sparse signal recovery from phaseless measurements via hard thresholding pursuit	6
Non-asymptotic bounds for discrete prolate spheroidal wave functions analogous with prolate spheroidal wave function bounds	6
Linearized Wasserstein dimensionality reduction with approximation guarantees	6