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 2022-05-01 to 2026-05-01.)

Article	Citations
On the numerical evaluation of the prolate spheroidal wave functions of order zero	91
Introduction to the Special Issue on Harmonic Analysis and Machine Learning	51
Kadec-type theorems for sampled group orbits	46
On the limits of neural network explainability via descrambling	44
A diffusion + wavelet-window method for recovery of super-resolution point-masses with application to single-molecule microscopy and beyond	42
Editorial Board	40
Spatiotemporal analysis using Riemannian composition of diffusion operators	40
Convergence of sparse grid Gaussian convolution approximation for multi-dimensional periodic functions	40
Scale dependencies and self-similar models with wavelet scattering spectra	40
Duality for neural networks through Reproducing Kernel Banach Spaces	37
Complete interpolating sequences for the Gaussian shift-invariant space	32
Dilational symmetries of decomposition and coorbit spaces	30
The theory of deep convolutional neural networks and a data approximation problem based on the fractional Fourier transform	25
Biorthogonal Greedy Algorithms in convex optimization	23
Signal reconstruction using determinantal sampling	23
Beurling dimension of spectra for a class of random convolutions on R<	22
Estimates on learning rates for multi-penalty distribution regression	22
AP-frames and stationary random processes	21
Unlimited sampling beyond modulo	21
A note on spike localization for line spectrum estimation	20
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks	19
Generalization error of random feature and kernel methods: Hypercontractivity and kernel matrix concentration	19
Error estimate of the u-series method for molecular dynamics simulations	18
Sharp error estimates for target measure diffusion maps with applications to the committor problem	18
Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning	17

Computing the proximal operator of the q-th power of the ℓ1,-norm for group sparsity	17
Editorial Board	16
Marcinkiewicz–Zygmund inequalities for scattered and random data on the q-sphere	15
Finite alphabet phase retrieval	14
Controlled learning of pointwise nonlinearities in neural-network-like architectures	14
A simple approach for quantizing neural networks	13
Eigenmatrix for unstructured sparse recovery	13
Editorial Board	12
Editorial Board	12
n-Best kernel approximation in reproducing kernel Hilbert spaces	12
Spatiospectral localization within the ball – studies on the influence of the spectral shape	12
Adaptive parameter selection for kernel ridge regression	11
Stable parameterization of continuous and piecewise-linear functions	11
A fractal uncertainty principle for the short-time Fourier transform and Gabor multipliers	11
Localization of operator-valued frames	11
Regularization of inverse problems by filtered diagonal frame decomposition	11
Gaussian random field approximation via Stein's method with applications to wide random neural networks	11
On the relation between Fourier and Walsh–Rademacher spectra for random fields	11
On the intermediate value property of spectra for a class of Moran spectral measures	10
An efficient spatial discretization of spans of multivariate Chebyshev polynomials	10
Divergence-free quasi-interpolation	10
Data-driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application	10
Direct interpolative construction of the discrete Fourier transform as a matrix product operator	10
Theoretical guarantees for low-rank compression of deep neural networks	10
A sufficient condition for mobile sampling in terms of surface density	10
Demystifying Carleson frames	9
An unbounded operator theory approach to lower frame and Riesz-Fischer sequences	9
Estimation under group actions: Recovering orbits from invariants	9
Non-negative sparse recovery at minimal sampling rate	9
Solving phase retrieval with random initial guess is nearly as good as by spectral initialization	8
Fundamental component enhancement via adaptive nonlinear activation functions	8
Lower bounds on the low-distortion embedding dimension of submanifolds of 8
Laplace-Beltrami operator on the orthogonal group in ambient (Euclidean) coordinates	8
On the accuracy of Prony's method for recovery of exponential sums with closely spaced exponents	8
Sparse free deconvolution under unknown noise level via eigenmatrix	8
The impact of smoothness of kernels and target functions on unsupervised covariate shift adaptation in RKHS	7
Synthesis-based time-scale transforms for non-stationary signals	7
Constructive subsampling of finite frames with applications in optimal function recovery	7
Optimal (α,d)-multi-completion of d-designs	7
Positive definite multi-kernels for scattered data interpolations	7
Weighted variation spaces and approximation by shallow ReLU networks	7
Dimension reduction, exact recovery, and error estimates for sparse reconstruction in phase space	7
Painless construction of unconditional bases for anisotropic modulation and Triebel-Lizorkin type spaces	7
Algebraic compressed sensing	7
Pattern recovery by SLOPE	7
A tighter generalization error bound for wide GCN based on loss landscape	7
Editorial Board	7
Generalization bounds for sparse random feature expansions	7
A unified approach to synchronization problems over subgroups of the orthogonal group	6
Permutation-invariant representations with applications to graph deep learning	6

Linearized Wasserstein dimensionality reduction with approximation guarantees	6
Universal approximation property of fully convolutional neural networks with zero padding	6
Editorial Board	6
Tikhonov regularization for Gaussian empirical gain maximization in RKHS is consistent	6
A one-bit, comparison-based gradient estimator	6
Assembly and iteration: Transition to linearity of wide neural networks	6
Non-asymptotic bounds for discrete prolate spheroidal wave functions analogous with prolate spheroidal wave function bounds	6
Uniform approximation of common Gaussian process kernels using equispaced Fourier grids	6
Frames by orbits of two operators that commute	6
The G-invariant graph Laplacian part II: Diffusion maps	6
The springback penalty for robust signal recovery	6
Sparsification of the regularized magnetic Laplacian with multi-type spanning forests	6
Editorial Board	6
Quantum wave packet transforms with compact frequency support: Implementations for wavelets and Gabor atoms	6