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 2020-05-01 to 2024-05-01.)

Article	Citations
Spectrality of self-affine Sierpinski-type measures on R	48
Adaptive synchrosqueezing transform with a time-varying parameter for non-stationary signal separation	47
Graph convolutional neural networks via scattering	43
Fractional Fourier transforms on L and applications	34
Aliasing error of the exp⁡(β<	34
Reproducing kernel Hilbert space compactification of unitary evolution groups	30
Stable super-resolution limit and smallest singular value of restricted Fourier matrices	28
Loss landscapes and optimization in over-parameterized non-linear systems and neural networks	28
Koopman spectra in reproducing kernel Hilbert spaces	23
Phase retrieval of real-valued signals in a shift-invariant space	22
Perspectives on CUR decompositions	22
Distributed kernel gradient descent algorithm for minimum error entropy principle	22
Time-scale-chirp_rate operator for recovery of non-stationary signal components with crossover instantaneous frequency curves	22
Uniqueness of STFT phase retrieval for bandlimited functions	22
Large data and zero noise limits of graph-based semi-supervised learning algorithms	21
Improved bounds for the eigenvalues of prolate spheroidal wave functions and discrete prolate spheroidal sequences	20
Wigner analysis of operators. Part I: Pseudodifferential operators and wave fronts	19
Optimal rates for spectral algorithms with least-squares regression over Hilbert spaces	19
Spectral convergence of graph Laplacian and heat kernel reconstruction in L∞ from random samples	18
ℓ1-Analysis minimization and generalized (co-)sparsity: When does recovery succeed?	18
A sharp upper bound for sampling numbers in L2	18
Signal separation based on adaptive continuous wavelet-like transform and analysis	17
Approximate support recovery of atomic line spectral estimation: A tale of resolution and precision	17
Generalization error of random feature and kernel methods: Hypercontractivity and kernel matrix concentration	16
High-order approximation rates for shallow neural networks with cosine and ReLU activation functions	15

Learning under (1 + ϵ)-moment conditions	15
On signal reconstruction from FROG measurements	15
Time-frequency transforms of white noises and Gaussian analytic functions	14
Maximum entropy models from phase harmonic covariances	14
Spectrality of generalized Sierpinski-type self-affine measures	14
Analysis of the ratio of ℓ1 and ℓ2 norms in compressed sensing	13
Low-rank matrix recovery via regularized nuclear norm minimization	13
Near-optimal performance bounds for orthogonal and permutation group synchronization via spectral methods	13
Wavelet thresholding for recovery of active sub-signals of a composite signal from its discrete samples	13
Random sampling and reconstruction of concentrated signals in a reproducing kernel space	12
Convex optimization in sums of Banach spaces	12
An edge driven wavelet frame model for image restoration	12
Wavelet characterization of Besov and Triebel–Lizorkin spaces on spaces of homogeneous type and its applications	12
A mathematical theory of the computational resolution limit in one dimension	12
Graph Fourier transform based on ℓ1 norm variation minimization	12
Sparse non-negative super-resolution — simplified and stabilised	12
Generalization bounds for sparse random feature expansions	11
Estimation under group actions: Recovering orbits from invariants	11
A necessary and sufficient condition for sparse vector recovery via ℓ1 − ℓ2 minimization	11
Gabor phase retrieval is severely ill-posed	11
High-dimensional sparse FFT based on sampling along multiple rank-1 lattices	11
Isotropic sparse regularization for spherical harmonic representations of random fields on the sphere	11
Defining the wavelet bispectrum	11
Improved spectral convergence rates for graph Laplacians on ε-graphs and k-NN graphs	10
Injectivity of Gabor phase retrieval from lattice measurements	10
Solving phase retrieval with random initial guess is nearly as good as by spectral initialization	10
The universal approximation theorem for complex-valued neural networks	10
Riesz transform associated with the fractional Fourier transform and applications in image edge detection	10
Compactly supported quasi-tight multiframelets with high balancing orders and compact framelet transforms	10
Quasi-projection operators in weighted L spaces	10
Rician noise removal via weighted nuclear norm penalization	9
Infinite dimensional compressed sensing from anisotropic measurements and applications to inverse problems in PDE	9
Group sparse recovery in impulsive noise via alternating direction method of multipliers	9
Complex best r-term approximations almost always exist in finite dimensions	9
Data-driven spatiotemporal modal decomposition for time frequency analysis	9
How to get high resolution results from sparse and coarsely sampled data	9
Dynamical sampling for shift-preserving operators	9
Regularization of inverse problems by filtered diagonal frame decomposition	8
Quasi-tight framelets with high vanishing moments derived from arbitrary refinable functions	8
Neural collapse under cross-entropy loss	8
Analysis of a direct separation method based on adaptive chirplet transform for signals with crossover instantaneous frequencies	8
Intertwining wavelets or multiresolution analysis on graphs through random forests	8
Sparse recovery in bounded Riesz systems with applications to numerical methods for PDEs	8
Disentangling modes with crossover instantaneous frequencies by synchrosqueezed chirplet transforms, from theory to application	8
Activation function design for deep networks: linearity and effective initialisation	8
A classification of anisotropic Besov spaces	8
A fast simple algorithm for computing the potential of charges on a line	8
Analysis and algorithms for ℓ-based semi-supervised learning on graphs	8
Differentially private SGD with non-smooth losses	7
Interpolating splines on graphs for data science applications	7

Harmonic analysis on directed graphs and applications: From Fourier analysis to wavelets	7
Wavelets on intervals derived from arbitrary compactly supported biorthogonal multiwavelets	7
Constructive subsampling of finite frames with applications in optimal function recovery	7
Multi-view kernel consensus for data analysis	7
A multiscale environment for learning by diffusion	7
Generalizing CoSaMP to signals from a union of low dimensional linear subspaces	7
Stable phase retrieval from locally stable and conditionally connected measurements	7
Transferability of graph neural networks: An extended graphon approach	6
Diffusion K-means clustering on manifolds: Provable exact recovery via semidefinite relaxations	6
Gaussian and sparse processes are limits of generalized Poisson processes	6
Understanding neural networks with reproducing kernel Banach spaces	6
A stochastic sparse representation: n-best approximation to random signals and computation	6
Phase retrieval using alternating minimization in a batch setting	6
Computing committors in collective variables via Mahalanobis diffusion maps	6
The recovery of complex sparse signals from few phaseless measurements	6
Multiresolution mode decomposition for adaptive time series analysis	6
Almost everywhere generalized phase retrieval	6
The diffusion geometry of fibre bundles: Horizontal diffusion maps	6
Capacity dependent analysis for functional online learning algorithms	6
Sparse signal recovery from phaseless measurements via hard thresholding pursuit	6