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 2021-11-01 to 2025-11-01.)

Article	Citations
Scale dependencies and self-similar models with wavelet scattering spectra	77
On the limits of neural network explainability via descrambling	55
Kadec-type theorems for sampled group orbits	41
Spatiotemporal analysis using Riemannian composition of diffusion operators	39
Introduction to the Special Issue on Harmonic Analysis and Machine Learning	38
On the numerical evaluation of the prolate spheroidal wave functions of order zero	35
Convergence of sparse grid Gaussian convolution approximation for multi-dimensional periodic functions	35
A diffusion + wavelet-window method for recovery of super-resolution point-masses with application to single-molecule microscopy and beyond	33
Duality for neural networks through Reproducing Kernel Banach Spaces	30
Editorial Board	29
Kernel conjugate gradient methods with random projections	29
Beurling dimension of spectra for a class of random convolutions on R<	29
Sharp error estimates for target measure diffusion maps with applications to the committor problem	28
On the optimal approximation of Sobolev and Besov functions using deep ReLU neural networks	24
Computing the proximal operator of the q-th power of the ℓ1,-norm for group sparsity	23
Unlimited sampling beyond modulo	21
AP-frames and stationary random processes	21
Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning	21
Dilational symmetries of decomposition and coorbit spaces	21
Error estimate of the u-series method for molecular dynamics simulations	21
On the evaluation of the eigendecomposition of the Airy integral operator	20
Biorthogonal Greedy Algorithms in convex optimization	19
Complete interpolating sequences for the Gaussian shift-invariant space	19
Estimates on learning rates for multi-penalty distribution regression	17
Generalization error of random feature and kernel methods: Hypercontractivity and kernel matrix concentration	17

A note on spike localization for line spectrum estimation	17
On a discrete transform of homogeneous decomposition spaces	16
A stochastic sparse representation: n-best approximation to random signals and computation	16
Dispersion, spreading and sparsity of Gabor wave packets for metaplectic and Schrödinger operators	16
Editorial Board	15
Marcinkiewicz–Zygmund inequalities for scattered and random data on the q-sphere	14
Controlled learning of pointwise nonlinearities in neural-network-like architectures	14
Irregular Gabor frames of Cauchy kernels	13
Finite alphabet phase retrieval	13
Gaussian random field approximation via Stein's method with applications to wide random neural networks	12
Eigenmatrix for unstructured sparse recovery	12
Editorial Board	12
Uniform recovery in infinite-dimensional compressed sensing and applications to structured binary sampling	12
A simple approach for quantizing neural networks	12
Adaptive parameter selection for kernel ridge regression	11
An efficient spatial discretization of spans of multivariate Chebyshev polynomials	11
A fractal uncertainty principle for the short-time Fourier transform and Gabor multipliers	11
n-Best kernel approximation in reproducing kernel Hilbert spaces	11
Data-driven optimal shrinkage of singular values under high-dimensional noise with separable covariance structure with application	11
On the number of faces and radii of cells induced by Gaussian spherical tessellations	11
Stable parameterization of continuous and piecewise-linear functions	11
On the relation between Fourier and Walsh–Rademacher spectra for random fields	10
On the accuracy of Prony's method for recovery of exponential sums with closely spaced exponents	10
On the intermediate value property of spectra for a class of Moran spectral measures	10
Solving phase retrieval with random initial guess is nearly as good as by spectral initialization	10
Regularization of inverse problems by filtered diagonal frame decomposition	10
An unbounded operator theory approach to lower frame and Riesz-Fischer sequences	10
Estimation under group actions: Recovering orbits from invariants	9
A sufficient condition for mobile sampling in terms of surface density	9
Direct interpolative construction of the discrete Fourier transform as a matrix product operator	9
Frames of translates for model sets	9
Divergence-free quasi-interpolation	9
Dimension reduction, exact recovery, and error estimates for sparse reconstruction in phase space	8
Weighted variation spaces and approximation by shallow ReLU networks	8
Lower bounds on the low-distortion embedding dimension of submanifolds of 8
Editorial Board	8
A tighter generalization error bound for wide GCN based on loss landscape	8
Laplace-Beltrami operator on the orthogonal group in ambient (Euclidean) coordinates	8
Sparse free deconvolution under unknown noise level via eigenmatrix	8
Synthesis-based time-scale transforms for non-stationary signals	8
Fundamental component enhancement via adaptive nonlinear activation functions	7
Permutation-invariant representations with applications to graph deep learning	7
Editorial Board	7
Positive definite multi-kernels for scattered data interpolations	7
Spectral analysis of weighted Laplacians arising in data clustering	7
Tikhonov regularization for Gaussian empirical gain maximization in RKHS is consistent	7
Optimal (α,d)-multi-completion of d-designs	7
A one-bit, comparison-based gradient estimator	7
Constructive subsampling of finite frames with applications in optimal function recovery	7
Algebraic compressed sensing	7

A unified approach to synchronization problems over subgroups of the orthogonal group	7
Spectral convergence of graph Laplacian and heat kernel reconstruction in L∞ from random samples	6
The springback penalty for robust signal recovery	6
Editorial Board	6
On a regularization of unsupervised domain adaptation in RKHS	6
Generalization bounds for sparse random feature expansions	6
The G-invariant graph Laplacian part II: Diffusion maps	6
Sparsification of the regularized magnetic Laplacian with multi-type spanning forests	6
Uniform approximation of common Gaussian process kernels using equispaced Fourier grids	6
Metric entropy limits on recurrent neural network learning of linear dynamical systems	6
Spectrality of generalized Sierpinski-type self-affine measures	6
Linearized Wasserstein dimensionality reduction with approximation guarantees	6
Frames by orbits of two operators that commute	6
Performance bounds of the intensity-based estimators for noisy phase retrieval	6
Non-asymptotic bounds for discrete prolate spheroidal wave functions analogous with prolate spheroidal wave function bounds	6
Sparse signal recovery from phaseless measurements via hard thresholding pursuit	6