Key papers

• When Can You Correct Distribution Drift in Temporal Graph Generation? A Sharpening--Drift Tension and an Impossibility for Observation-Based Correction (2026)
  Tianpeng Li et al.
  5.89
• Explicit Iteration Complexity of Exact Data-Driven Inverse Optimization for Integer Linear Programs (2026)
  Akira Kitaoka
  5.49
• Selective Impairment of Motor Recovery from Typing Errors in Parkinson's Disease: A Survival Analysis (2026)
  Navin Bondade
  5.49
• ScoreShield: Differentially Private Release of Similarity Scores (2026)
  Behrooz Razeghi et al.
  5.49
• Weight-norm Criticality: A Mechanism for Loss Spikes Induced by the Normalization and Weight Decay (2026)
  Xiaolong Li et al.
  5.01
• Optimal use of a black-box learner in semiparametric estimation (2026)
  Yihong Gu
  5.01
• Natural Invariant Measures for Chaotic Game Dynamics: Finding Order in Chaos (2026)
  Jakub Bielawski et al.
  5.01
• Distributional Determinantal Point Process for Repulsive Clustering of Distributions (2026)
  Khai Nguyen et al.
  5.01
• Interventional Score Geometry for Causal Inference (2026)
  Mojtaba Eslami
  5.01
• Convergence analysis of a family of Zermelo-type iterations for the Bradley--Terry model (2026)
  Ruijian Han et al.
  5.01
• Learning Bidirectional Causal Interactions with Heteroscedastic Neural Networks (2026)
  Masahiro Tanaka
  5.01
• Correlation-Aware and Gaussianity-Preserving Robust Latent Angular Watermarking for Diffusion Models (2026)
  Yebin Zheng et al.
  5.01
• Learning Ergodic Dynamical Systems from a Finite Trajectory (2026)
  Oleksii Kachaiev et al.
  5.01
• The V-fold jackknife for semiparametric inference: variance estimation, confidence intervals, and simultaneous confidence bands (2026)
  Yi Li et al.
  5.01
• A Resolution of the SS--RS--GD Inequalities (2026)
  Binghui Peng
  5.01
• Learning from the Descent Direction: Adaptive Gradient Descent under One-Sided H\"older Regularity (2026)
  Arzu Ahmadova et al.
  5.01
• Nesterov acceleration in optimizing over probability measures (2026)
  Jiaqi Tang et al.
  5.01
• Characterizing Arbitrary Lindbladian Dynamics with a Few Pauli Measurements (2026)
  Taiqi Zhou et al.
  5.01
• Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions (2026)
  Getachew K. Befekadu
  5.01
• Transfer Learning in High-Dimensional Clustering: Minimax Thresholds and Applications in Single-Cell Data (2026)
  Abhinav Chakraborty et al.
  5.01
• A Foundational Perspective for Partitional Clustering on Networks (2026)
  Derya Ipek Eroglu et al.
  5.01
• Sample Complexities of Estimating Gumbel--Max Watermark Proportions with and without Reduction to Pivotal Statistics (2026)
  Shuwen Chai et al.
  4.39
• Data-Poisoning Audits for Causal Effect Estimation (2026)
  Kwangho Kim
  4.39
• A Structure-Adaptive Random Feature Method for High-Dimensional Elliptic PDEs (2026)
  Jiale Linghu et al.
  4.39
• Instance Hardness-Based Relevance for Imbalanced Regression (2026)
  Vitor M. Leitao et al.
  4.39
• Interpretable Fuzzy Rule-Based Regression Extension for Ex-Fuzzy Library (2026)
  Cayan Deniz Kucuktopana et al.
  4.39
• Lipschitzian SLLNs for random functions (2026)
  Lai Tian et al.
  4.39
• Inducing Comparability of Factorised Probability Distributions (2026)
  Jan Speller et al.
  4.39
• Fisher Widths: Local Learning Geometry and Anisotropic Recovery (2026)
  Vu Khac Ky
  4.39
• Measuring the Dependency Gap: Diagnosing Inter-Column Fidelity in Tabular Generative Models (2026)
  Jie Zhang
  4.39
• Data eccentricity, asymptotics of Gaussian RBF reproducing kernel Hilbert space, and kernel PCA (2026)
  Sergio A. Alvarez
  4.39
• Scaling Laws for Classical Machine Learning on Tabular Data: A Benchmark Study (2026)
  Kaihua Ding
  4.39
• From Score Approximation to Distribution Approximation in Score-Based Diffusion Models (2026)
  Lan V. Truong
  4.39
• TLRNet: Estimating Individual Treatment Effect based on Local Information and Single Learner Structure (2026)
  Ali Haghpanah Jahromi et al.
  4.39
• Mirror Langevin diffusions: Convergence rates and Markov chain approximations (2026)
  Benjamin Capdeville et al.
  4.39
• Beyond Directed Acyclic Graphs: Causal Zeros and Causal Differential Equations (2026)
  Sergei V. Kalinin
  4.39
• Discrepancy-Rounded Fair Bandits with Static and Time-Varying Exposure Floors (2026)
  Ibne Farabi Shihab et al.
  4.39
• On the Order-Conditional Optimality of Gaffke's Bound (2026)
  George Bissias et al.
  4.39
• An Explicit Counterexample to Stanley's Rankwise Lower-Bound Conjecture for Differential Posets (2026)
  Xinan Dai et al.
  4.39
• Mini-batch Noise Lowers Sharpness via Dominant-Subspace Fluctuations (2026)
  Junho So et al.
  4.39
• Diffusion-Guided Search via Exponential Tilting (DiffTilt): An Application to Falsification of Safety-Critical Systems (2026)
  Tanmay Khandait et al.
  4.39
• Anytime-Valid Confirmation of Covariate Balance for Prespecified Corrections (2026)
  Seungjin Choi
  4.39
• Data-Driven Diffusion Processes on Differential Forms via the Projected Ambient Connection Laplacian (2026)
  Alvaro Almeida Gomez et al.
  4.39
• Learning Asymptotics with Convergence-Rate Guarantees using Linear Least Squares (2026)
  Christos N. Efrem
  4.39
• Online Fair Division with Budget Constraints (2026)
  Saar Cohen et al.
  4.39
• A Statistical Difference between Single-Layer Learning and Hierarchical Learning in Wide Neural Networks (2026)
  Sumio Watanabe
  4.39
• Local Regularization Does Not Characterize Multiclass PAC Learnability (2026)
  Eric Hou
  4.39
• Learning switched non-linear dynamical systems from a single trajectory (2026)
  Sunny G. W. Wang et al.
  4.39
• Distributional Split Criteria for Random Forests: Extensions, Shrinkage, and the Robustness of Mean Splitting (2026)
  Silas Koemen
  4.39
• The Phase Transition in Online PCA Depends on $n/d\log(d)$, not $n/d$ (2026)
  Apratim Dey
  4.39
• Structural Loss Metrics for Tensor Approximation via Matrix Low-Rank Approximation (2026)
  Hiroki Hasegawa
  4.39
• The Zero Pattern of a Design Matrix Drives Multiple Descent in Over-parameterized Regression (2026)
  Kevin Han Huang et al.
  4.39
• On Non-Stationary Dynamic Pricing: Adaptivity and Optimality (2026)
  Feiyu Jiang et al.
  4.39
• Minimax Lower Bounds of Kernel Discrepancy Estimation: MMD, HSIC, KSD (2026)
  Jose Cribeiro-Ramallo et al.
  4.39
• Why does Greedy Search produce Optimal Clustering Outcomes? A Fixed-Core Assignment Theory (2026)
  Kaifeng Zhang et al.
  4.39
• Decision trees, Frobenius traces, and Weierstrass coefficients of elliptic curves (2026)
  Barinder S. Banwait et al.
  4.39
• Stochastic Counterdiabatic Driving via Biorthogonal Liouvillian Eigenmodes (2026)
  Sandeep Suresh Cranganore et al.
  4.39
• Low-Rank Dependence Decomposition via Accelerated Symmetric Non-negative Matrix Factorization (2026)
  Lavinia Ghita et al.
  4.39
• Learning Distributions from Multiple Data Providers (2026)
  Jon Kleinberg et al.
  4.39
• A Path Integral Model of Cognition (2026)
  Haruki Emori et al.
  4.39