OOIR: Observatory of International Research

Papers

(The TQCC of SIAM Journal on Mathematics of Data Science is 4. 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 2022-08-01 to 2026-08-01.)

Article	Citations
Spectral Barron Space for Deep Neural Network Approximation	37
A Simple and Optimal Algorithm for Strict Circular Seriation	29
Taming Neural Networks with TUSLA: Nonconvex Learning via Adaptive Stochastic Gradient Langevin Algorithms	23
Learning Functions Varying along a Central Subspace	22
Efficient Algorithms for Regularized Nonnegative Scale-Invariant Low-Rank Approximation Models	19
Block Majorization Minimization with Extrapolation and Application to \({\beta }\)-NMF	17
On the Inconsistency of Kernel Ridgeless Regression in Fixed Dimensions	17
Poisson Reweighted Laplacian Uncertainty Sampling for Graph-Based Active Learning	16
Deep Block Proximal Linearized Minimization Algorithm for Nonconvex Inverse Problems	15
New Equivalences between Interpolation and SVMs: Kernels and Structured Features	15
Resolving the Mixing Time of the Langevin Algorithm to Its Stationary Distribution for Log-Concave Sampling	14
Randomized Nyström Approximation of Non-negative Self-Adjoint Operators	14
Online Machine Teaching under Learner Uncertainty: Gradient Descent Learners of a Quadratic Loss	13
Detection and Estimation of Vertexwise Latent Position Shifts Across Networks	13
A Note on the Regularity of Images Generated by Convolutional Neural Networks	13
Wassmap: Wasserstein Isometric Mapping for Image Manifold Learning	11
Nonlinear Tomographic Reconstruction via Nonsmooth Optimization	11
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature	10
Nonbacktracking Spectral Clustering of Nonuniform Hypergraphs	10
Nonlinear Meta-learning Can Guarantee Faster Rates	10
Safe Rules for the Identification of Zeros in the Solutions of the SLOPE Problem	10
Can We Spot a Fake?	10
Function-Space Optimality of Neural Architectures with Multivariate Nonlinearities	9
A Notion of Uniqueness for the Adversarial Bayes Classifier	9
Asymptotics of the Sketched Pseudoinverse	9

Learning Memory Kernels in Generalized Langevin Equations	9
Stochastic Variance-Reduced Majorization-Minimization Algorithms	9
Scalable Tensor Methods for Nonuniform Hypergraphs	9
Group-Invariant Tensor Train Networks for Supervised Learning	8
Covariance Alignment: From Maximum Likelihood Estimation to Gromov–Wasserstein	8
Inverse Evolution Layers: Physics-Informed Regularizers for Image Segmentation	8
The GenCol Algorithm for High-Dimensional Optimal Transport: General Formulation and Application to Barycenters and Wasserstein Splines	8
The Sample Complexity of Sparse Multireference Alignment and Single-Particle Cryo-Electron Microscopy	8
Finite-Time Analysis of Natural Actor-Critic for POMDPs	7
Random Multitype Spanning Forests for Synchronization on Sparse Graphs	7
Supervised Gromov–Wasserstein Optimal Transport with Metric-Preserving Constraints	7
Learning Algorithm Hyperparameters for Fast Parametric Convex Optimization	7
The Geometric Median and Applications to Robust Mean Estimation	7
On Neural Network Approximation of Ideal Adversarial Attack and Convergence of Adversarial Training	6
Optimal Dorfman Group Testing for Symmetric Distributions	6
Convergence of Gradient Descent for Recurrent Neural Networks: A Nonasymptotic Analysis	6
Bi-Invariant Dissimilarity Measures for Sample Distributions in Lie Groups	6
Numerical Considerations and a new implementation for invariant coordinate selection	6
Computing Wasserstein Barycenters via Operator Splitting: The Method of Averaged Marginals	5
LASSO Reloaded: A Variational Analysis Perspective with Applications to Compressed Sensing	5
Memory Capacity of Two Layer Neural Networks with Smooth Activations	5
Efficient Identification of Butterfly Sparse Matrix Factorizations	5
Phase Retrieval with Semialgebraic and ReLU Neural Network Priors	5
Post-training Quantization for Neural Networks with Provable Guarantees	5
ABBA Neural Networks: Coping with Positivity, Expressivity, and Robustness	5
Operator Shifting for General Noisy Matrix Systems	5
Spectral Properties of Elementwise-Transformed Spiked Matrices	4
A Priori Estimates for Deep Residual Network in Continuous-Time Reinforcement Learning	4
Optimality Conditions for Nonsmooth Nonconvex-Nonconcave Min-Max Problems and Generative Adversarial Networks	4
Fast Kernel Summation in High Dimensions via Slicing and Fourier Transforms	4
Stability of Sequential Lateration and of Stress Minimization in the Presence of Noise	4
Stochastic Gradient Descent for Streaming Linear and Rectified Linear Systems with Adversarial Corruptions	4
Robust Reinforcement Learning with Dynamic Distortion Risk Measures	4
Complete and Continuous Invariants of 1-Periodic Sequences in Polynomial Time	4
Accelerated and Instance-Optimal Policy Evaluation with Linear Function Approximation	4
Precise Asymptotics for Spectral Methods in Mixed Generalized Linear Models	4
Stable Gradient-Adjusted Root Mean Square Propagation on Least Squares Problem	4
Multifidelity Covariance Estimation via Regression on the Manifold of Symmetric Positive Definite Matrices	4
Adaptive Joint Distribution Learning	4
HADES: Fast Singularity Detection with Local Measure Comparison	4
KL Convergence Guarantees for Score Diffusion Models under Minimal Data Assumptions	4