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Statistics, Machine Learning papers, 2026-03-01 to 2026-08-31

Every paper in the arxiv corpus whose primary field is the arXiv category stat.ML, submitted inside this window. An impact prediction on exactory states a citation rank against this population.

Corpus
arxiv
Papers
1,406
Collected
7 Sept 2026

Papers

  1. Hypercomplex Widely Linear Processing: Fundamentals for Quaternion Machine Learning2603.11835 · 12 Mar 2026
  2. Wasserstein Gradient Flows for Batch Bayesian Optimal Experimental Design2603.12102 · 12 Mar 2026
  3. Uncovering Locally Low-dimensional Structure in Networks by Locally Optimal Spectral Embedding2603.11965 · 12 Mar 2026
  4. Probabilistic Joint and Individual Variation Explained (ProJIVE) for Data Integration2603.12351 · 12 Mar 2026
  5. EB-RANSAC: Random Sample Consensus based on Energy-Based Model2603.12525 · 12 Mar 2026
  6. Batched Kernelized Bandits: Refinements and Extensions2603.12627 · 13 Mar 2026
  7. Variational Garrote for Sparse Inverse Problems2603.12562 · 13 Mar 2026
  8. VecMol: Vector-Field Representations for 3D Molecule Generation2603.12734 · 13 Mar 2026
  9. A theory of learning data statistics in diffusion models, from easy to hard2603.12901 · 13 Mar 2026
  10. EmDT: Embedding Diffusion Transformer for Tabular Data Generation in Fraud Detection2603.13566 · 13 Mar 2026
  11. Robust Automatic Differentiation of Square-Root Kalman Filters via Gramian Differentials2603.13559 · 13 Mar 2026
  12. Filtered Spectral Projection for Quantum Principal Component Analysis2603.13441 · 13 Mar 2026
  13. Standard Acquisition Is Sufficient for Asynchronous Bayesian Optimization2603.13501 · 13 Mar 2026
  14. Holographic Invariant Storage: Design-Time Safety Contracts via Vector Symbolic Architectures2603.13558 · 13 Mar 2026
  15. Robust Sequential Tracking via Bounded Information Geometry and Non-Parametric Field Actions2603.13613 · 13 Mar 2026
  16. Maximin Robust Bayesian Experimental Design2603.14094 · 14 Mar 2026
  17. An Interpretable and Stable Framework for Sparse Principal Component Analysis2603.13806 · 14 Mar 2026
  18. Conditional flow matching for physics-constrained inverse problems with finite training data2603.14135 · 14 Mar 2026
  19. When Should Humans Step In? Optimal Human Dispatching in AI-Assisted Decisions2603.13688 · 14 Mar 2026
  20. Beyond Distance: Quantifying Point Cloud Dynamics with Persistent Homology and Dynamic Optimal Transport2603.15683 · 15 Mar 2026
  21. Convergence of Two Time-Scale Stochastic Approximation: A Martingale Approach2603.14481 · 15 Mar 2026
  22. AR-Flow VAE: A Structured Autoregressive Flow Prior Variational Autoencoder for Unsupervised Blind Source Separation2603.14441 · 15 Mar 2026
  23. Power-Law Spectrum of the Random Feature Model2603.14578 · 15 Mar 2026
  24. Learning-to-Defer with Expert-Conditional Advice2603.14324 · 15 Mar 2026
  25. Analyzing Error Sources in Global Feature Effect Estimation2603.15057 · 16 Mar 2026
  26. The Sampling Complexity of Condorcet Winner Identification in Dueling Bandits2603.15189 · 16 Mar 2026
  27. Bayesian Symbolic Regression for Missing Physics2603.14918 · 16 Mar 2026
  28. Estimating Staged Event Tree Models via Hierarchical Clustering on the Simplex2603.15568 · 16 Mar 2026
  29. Learnability with Partial Labels and Adaptive Nearest Neighbors2603.15781 · 16 Mar 2026
  30. Persistence Spheres: a Bi-continuous Linear Representation of Measures for Partial Optimal Transport2603.15384 · 16 Mar 2026
  31. Learning to Recall with Transformers Beyond Orthogonal Embeddings2603.15923 · 16 Mar 2026
  32. Active Seriation: Efficient Ordering Recovery with Statistical Guarantees2603.15336 · 16 Mar 2026
  33. Preconditioned One-Step Generative Modeling for Bayesian Inverse Problems in Function Spaces2603.14798 · 16 Mar 2026
  34. Kriging via variably scaled kernels2603.16950 · 16 Mar 2026
  35. Spatio-temporal probabilistic forecast using MMAF-guided learning2603.15055 · 16 Mar 2026
  36. Scalable Simulation-Based Model Inference with Test-Time Complexity Control2603.15292 · 16 Mar 2026
  37. Self-Regularized Learning Methods2603.17160 · 17 Mar 2026
  38. Safe Distributionally Robust Feature Selection under Covariate Shift2603.16062 · 17 Mar 2026
  39. Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing2603.16829 · 17 Mar 2026
  40. Deep Adaptive Model-Based Design of Experiments2603.16146 · 17 Mar 2026
  41. When Marginals Match but Structure Fails: Covariance Fidelity in Generative Models2603.17041 · 17 Mar 2026
  42. rSDNet: Unified Robust Neural Learning against Label Noise and Adversarial Attacks2603.17628 · 18 Mar 2026
  43. A Noise Sensitivity Exponent Controls Large Statistical-to-Computational Gaps in Single- and Multi-Index Models2603.17896 · 18 Mar 2026
  44. Consistency of the $k$-Nearest Neighbor Regressor under Complex Survey Designs2603.17551 · 18 Mar 2026
  45. ResNets of All Shapes and Sizes: Convergence of Training Dynamics in the Large-scale Limit2603.18168 · 18 Mar 2026
  46. Mirror Descent on Riemannian Manifolds2603.17527 · 18 Mar 2026
  47. Starting Off on the Wrong Foot: Pitfalls in Data Preparation2603.18190 · 18 Mar 2026
  48. A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materials2603.18225 · 18 Mar 2026
  49. Gaussian Process Limit Reveals Structural Benefits of Graph Transformers2603.17569 · 18 Mar 2026
  50. On the Peril of (Even a Little) Nonstationarity in Satisficing Regret Minimization2603.18514 · 19 Mar 2026
  51. Pseudo-Labeling for Unsupervised Domain Adaptation with Kernel GLMs2603.19422 · 19 Mar 2026
  52. Statistical Testing Framework for Clustering Pipelines by Selective Inference2603.18413 · 19 Mar 2026
  53. Multi-Domain Empirical Bayes for Linearly-Mixed Causal Representations2603.18404 · 19 Mar 2026
  54. Subspace Projection Methods for Fast Spectral Embeddings of Evolving Graphs2603.19439 · 19 Mar 2026
  55. SRRM: Improving Recursive Transport Surrogates in the Small-Discrepancy Regime2603.18781 · 19 Mar 2026
  56. Kernel Single-Index Bandits: Estimation, Inference, and Learning2603.18938 · 19 Mar 2026
  57. Fast and Interpretable Autoregressive Estimation with Neural Network Backpropagation2603.19041 · 19 Mar 2026
  58. Precise Performance of Linear Denoisers in the Proportional Regime2603.18483 · 19 Mar 2026
  59. Revisiting OmniAnomaly for Anomaly Detection: performance metrics and comparison with PCA-based models2603.18985 · 19 Mar 2026
  60. Near-Equivalent Q-learning Policies for Dynamic Treatment Regimes2603.19440 · 19 Mar 2026
  61. Unified Taxonomy for Multivariate Time Series Anomaly Detection using Deep Learning2603.18941 · 19 Mar 2026
  62. A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Sufficient Convergence Conditions and Mixing Time Analysis under Gaussian Targets2603.18640 · 19 Mar 2026
  63. The Exponentially Weighted Signature2603.19198 · 19 Mar 2026
  64. Decorrelation, Diversity, and Emergent Intelligence: The Isomorphism Between Social Insect Colonies and Ensemble Machine Learning2603.20328 · 20 Mar 2026
  65. Operator Learning for Smoothing and Forecasting2603.20359 · 20 Mar 2026
  66. CogFormer: Learn All Your Models Once2603.20520 · 20 Mar 2026
  67. Measure flow path recovery in Bayes Hilbert spaces2603.20329 · 20 Mar 2026
  68. Explainable cluster analysis: a bagging approach2603.19840 · 20 Mar 2026
  69. Comprehensive Description of Uncertainty in Measurement for Representation and Propagation with Scalable Precision2603.20365 · 20 Mar 2026
  70. Graph-Informed Adversarial Modeling: Infimal Subadditivity of Interpolative Divergences2603.20025 · 20 Mar 2026
  71. On the role of memorization in learned priors for geophysical inverse problems2603.19629 · 20 Mar 2026
  72. PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA2603.23547 · 20 Mar 2026
  73. A two-step sequential approach for hyperparameter selection in finite context models2603.19736 · 20 Mar 2026
  74. Minimax Generalized Cross-Entropy2603.19874 · 20 Mar 2026
  75. Deep Autocorrelation Modeling for Time-Series Forecasting: Progress and Prospects2603.19899 · 20 Mar 2026
  76. Model Selection and Parameter Estimation for Multidimensional Gaussian Mixture Models with a Common Covariance Matrix2603.19657 · 20 Mar 2026
  77. Active Inference for Physical AI Agents -- An Engineering Perspective2603.20927 · 21 Mar 2026
  78. Stability of Sequential and Parallel Coordinate Ascent Variational Inference2603.20929 · 21 Mar 2026
  79. High-dimensional online learning via asynchronous decomposition: Non-divergent results, dynamic regularization, and beyond2603.20696 · 21 Mar 2026
  80. Experimental Design for Missing Physics2604.01231 · 21 Mar 2026
  81. LassoFlexNet: Flexible Neural Architecture for Tabular Data2603.20631 · 21 Mar 2026
  82. Sinkhorn Based Associative Memory Retrieval Using Spherical Hellinger Kantorovich Dynamics2603.20656 · 21 Mar 2026
  83. Auto-differentiable data assimilation: Co-learning of states, dynamics, and filtering algorithms2603.20891 · 21 Mar 2026
  84. Hard labels sampled from sparse targets mislead rotation invariant algorithms2603.20967 · 21 Mar 2026
  85. Interpretable Operator Learning for Inverse Problems via Adaptive Spectral Filtering: Convergence and Discretization Invariance2603.20602 · 21 Mar 2026
  86. Stochastic approximation in non-markovian environments revisited2603.21091 · 22 Mar 2026
  87. Domain Elastic Transform: Bayesian Function Registration for High-Dimensional Scientific Data2603.21235 · 22 Mar 2026
  88. Accelerate Vector Diffusion Maps by Landmarks2603.21247 · 22 Mar 2026
  89. Closed-form conditional diffusion models for data assimilation2603.21291 · 22 Mar 2026
  90. Gradient Descent with Projection Finds Over-Parameterized Neural Networks for Learning Low-Degree Polynomials with Nearly Minimax Optimal Rate2603.21062 · 22 Mar 2026
  91. Generalized Discrete Diffusion from Snapshots2603.21342 · 22 Mar 2026
  92. Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees2603.22355 · 22 Mar 2026
  93. Time-adaptive functional Gaussian Process regression2603.21144 · 22 Mar 2026
  94. SPDE Methods for Nonparametric Bayesian Posterior Contraction and Laplace Approximation2603.22468 · 23 Mar 2026
  95. Structural Concentration in Weighted Networks: A Class of Topology-Aware Indices2603.21918 · 23 Mar 2026
  96. Overfitting and Generalizing with (PAC) Bayesian Prediction in Noisy Binary Classification2603.22644 · 23 Mar 2026
  97. Privacy-Preserving Reinforcement Learning from Human Feedback via Decoupled Reward Modeling2603.22563 · 23 Mar 2026
  98. Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data2603.22050 · 23 Mar 2026
  99. CoNBONet: Conformalized Neuroscience-inspired Bayesian Operator Network for Reliability Analysis2603.21678 · 23 Mar 2026
  100. High-Resolution Tensor-Network Fourier Methods for Exponentially Compressed Non-Gaussian Aggregate Distributions2603.23106 · 24 Mar 2026