TBD

Nonparametric Estimators of Nonstationary Densities of Streaming Data

Bridging Minds and Machines: Rethinking Embodied Intelligence and Agentic AI

Counting Cycles with AI

Dynamic Topic Modeling with a Higher-Order Hypergraphical Representation

Reinforcement Learning in the Physical World

Naive and Optimal Portfolios Reconciled: A Golden Criterion

Few-Shot Personalization for Nonparametric Regression with Minimax Optimality

Statistical Inference for Large Potts Models

Stance Draft: How AI Middlemen Change What We Mean

Advances in Causal Inference and Adaptive Learning

Limit Theorems for Network Data without Metric Structure

Time-Varying Factor-Augmented Forecasting Regressions with Nonstationarity

Generalized Tensor Completion with Non-Random Missingness

Heterogeneous Multisource Transfer Learning via Model Averaging for Positive-Unlabeled Data

SpecTr-GBV: Multi-Draft Block Verification Accelerating Speculative Decoding

Large Scale Time Series Modeling and Forecasting by Neural Networks

Multiple Instance Learning for Multi-Label Data

LUMEN: A Large-Language-Model Guided Unified Multimodal Framework for Robust Prediction of Pulmonary Dysfunction

新时代人工智能赋能传染病监测预警的理论与实践

Intrinsic Riemannian Functional Sufficient Dimension Reduction and Beyond

Assessing Spatial Transmission Risk of Respiratory Infectious Diseases Across Urban Tiers in China: A Modelling Study

改写乙肝临床指南的真实世界数据建模分析

Electronic Health Record Foundation Models, Intelligent Agents, and Data Governance Frameworks

Modeling and Predicting Single-Cell Multi-Gene Perturbation Responses

A General-Purpose Healthcare System Based on Multi-Agent Intelligence

Algorithm-Dependent Learning Analysis of Over-Parameteried Neural Networks

Condensation Sheds Light to the Mathematical Foundation of Deep Neural Networks

A Functional Perspective for Understanding Neural Scaling Laws

The Phi Curve: Generalization Under Suitable Model Capacities in Modern Machine Learning-From Deterministic Equivalence to Function Spaces

Data Optimization for LLM Mid-Training and Post-Training

分数ARIMA过程的阶选择

On Phase Transition of a Multi Particle Pool Model

Shape of Large Feynman Cycles under BEC

Statistical Learning Problems in IPS: Learning Multi‑Type Heterogeneous Interacting Particle Systems

From Nonparametric Statistics to LLM Reasoning

What Should Post-Training Optimize? A Test-Time Scaling Law Perspective

Acceleration for Diffusion Models: Theory and Practice

The Statistical Price of Few Updates: Efficiency and Adaptivity in Batched Contextual Bandits

Nonlinear Alignment and Joint Embedding of High-Dimensional Data

Aggregating Dependent Signals: Validity and Power of Heavy-Tailed Combination Tests

Data Reconstruction: Identifiability and Optimization with Sample Splitting

A Model-Agnostic Ensemble Framework for Feature Selection via Adaptive Minipatch Subsampling

Sampling Error Bounds for the Denoising Diffusion Probabilistic Model via the Föllmer Process

Gaussian Fluctuations of Generalized U-Statistics and Subgraph Counting in the Binomial Random-Connection Model

Decay of Correlations and Limit Theorems for Random Intermittent Dynamical Systems

Non-Coincidence of Critical Points for Directed Polymers on Percolation Clusters

Multi-Task with Auxiliary Information for Massive Data and Applications

Fixed-k Inference for Explosive Drift

Asset Pricing Models with Network Effects

Prediction-Powered Linear Regression: A Balance between Interpretation and Prediction

Privacy-Preserving Multi-Source Transfer Learning for Credit Risk Prediction with Mixture Cure Models

中国城市经济增长的收敛性：来自284个城市及六大区域的证据

Connected Space, Vibrant City: The Impact of Public Service Accessibility on Service Consumption Vitality

Gaussianized Design Optimization for Covariate Balance in Randomized Experiments

Efficient Imputation Methods in Functional Structural Equation Model with Missing Data

零售业数字化转型对创新影响研究

社会核算矩阵稳态均衡模型研究

基于SEEA-EA海洋生态系统核算的国际标准、国外实践及启示

Precision Matrix Estimation for Multiple Compositional Vectors

Estimation for Partially Time-Varying Spatial Autoregressive Panel Data Model under Linear Constraints

Learning Sparse Support under Differential Privacy: Minimax Rates and Adaptive Algorithms

Differentially Private Minimax and Adaptive Bandable Covariance Matrix Estimation

Private Decentralized Federated Learning with Random Walk

Statistical Inference for Differentially Private Stochastic Gradient Descent

Knockoffs Inference under Privacy Constraints

Training-Free Multi-Agent Language Models

A Sparse Learning Framework for High-Dimensional Newsvendor under Privacy Constraints

Adapting to Noise Tails in Private Linear Regression

Testing for Granger Causality in Extreme Risk: A Two-Stage Generalized Cross-Spectral Approach

Network Analysis of Business Cycle Synchronisation

Forecasting Global Economy with SIGMAR: Sparsity-Induced Global Matrix AutoRegressive Model

Pairs Trading: A Change Point Perspective

Accent Matters: Communication Costs and Information Content in Analyst-Manager Dialogue

USAD: Uncertainty-Aware Statistical Adversarial Detection

Digital Twin for Behavior Change Interventions: A Case Study on HeartSteps Trials

Spatial-Sign Based High Dimensional Change Point Inference

A Successive Classification Learning for Estimating Quantile Optimal Treatment Regimes

Model-Free Checking Meets Cross-Domain Data: A Transfer Learning Approach

AI Safe: Statistical Methods for Security Protection from Small to Large Models

Location-Scale Quantile Regression with Functional Responses

A Bayesian Nonparametric Framework for Private, Fair, and Balanced Tabular Data Synthesis

Generalized Difference-in-Differences with Binary Outcomes

Double Machine Learning of Continuous Treatment Effects with General Instrumental Variables

A General Framework for Fair and Robust Regression

Harnessing Synthetic Data from Generative AI for Statistical Inference

Enhancing Protein Sequence Analysis with Synthetic Data and Foundation Models

LLM-Powered Deep Panel Modeling

Generative AI on Smooth Manifold

High-Dimensional Online Learning via Asynchronous Decomposition

求解高维问题的机器学习算法

Sampling Complexity of Temporal Difference and PPO in RKHS

Safeguarding Transfer Learning: An Adaptive Testing Approach for Structural Correctness and Functional Similarity

Estimation of Treatment Effects Without Ignorability Using Observational Studies

Not Every Factor Has Its Momentum

Testing Asset Pricing Factor Models: An Out-of-Sample Perspective

Granular Instrumental Variables: Estimation and Inference

Prediction-Powered Inference for AI-Based Phenotyping from Maize Field Images

Bregman Projection for Calibration Estimation in Survey Sampling

粒数据理论：面向事件完整性的数据治理数理框架与高质量数据集建设

Gene Ontology DAG-Aware Conformal FDR Control for Multi-Label Protein Function Prediction: A Maize Application

Unsupervised Federated Multi-Task Learning for Heterogeneous Tasks

SMS: Symmetric Mediation Statistics for Powerful High-Dimensional Mediation Analysis

Optimizing Dynamic Treatment Regimes under Spatial Interference: Evidence from COVID-19 School Closures

Hierarchical Projection for Adaptive Knowledge Transfer

When Less Is More: Binary Feedback Can Outperform Ordinal Comparisons in Ranking Recovery

Penalized Network Cross-Validation for Nested Models by Edge-Sampling

Inference for Network-Linked Data with Latent Position

A Generalized Network Autoregressive Model with Endogenous Aggregation and Heterogeneous Influence

Imperfect Extreme Ranked Set Sampling Design: A Framework for Robust and Efficient Inference

面向视频数据的抽样调查设计与预测增强推断方法研究

Research on Dual-System Estimator Based on Census and Mobile Phone Number Data

Design and Application of Dynamic Composite Sampling Method Based on the Occurrence Location of Economic Activities

Site-Varying Spatial Autoregression: Spatial Heterogeneity and Model Uncertainty

Model Averaging for Support Vector Classifier

Generalized Transfer Learning Based on Mallows Model Averaging

Combining Pre-Trained Large Models Based on Localized Model Averaging

Nodal Covariate Selection for Community Structures

Common Component Recovery in Heterogeneous Chain-Linked Multiple Matrices

Split Pseudo-Likelihood for Mixed Membership Stochastic Blockmodels

A General Exposure-Mapping-Agnostic Framework for Causal Inference under Interference Leveraging Two-Stage Randomization

TBD

Optimal Clustering by Lloyd Algorithm for Low-Rank Mixture Model

混合动态随机块模型下离散时间时序网络的快速社区检测

Triple-Dyad Ratio Estimation for the p1 Model

To Split or Not to Split: Valid Inference and Adaptive Stopping for Graph Segmentation

Interval Localization with Error Rate Control in Multiple Change-Point Analysis

Powerful Derandomized Knockoff: A Powerful and Reproducible FDR Control Approach

Mediation Analysis with Parallel Multiple Mediators: Missing Not at Random

FDR Control and Statistical Power for High-Dimensional Semiparametric Transformation Models

Optimal Estimators and Tests for Reciprocal Effects

Group-Sparse Smoothing for Longitudinal Models with Time-Varying Coefficients

基于 Huber 损失的函数型数据稳健网络估计

Adaptive Penalized Doubly Robust Regression for Longitudinal Data

Stable Multi-Surrogate Transformation for Robust and Generalizable Surrogacy

静动态功能梯度视角下的自闭症谱系障碍层级脑网络与状态转换异常研究

Assessment of Surrogacy Heterogeneity via a Logistic-Normal Mixture Model

Locally-Calibrated Split Conformal Prediction

Distributed Tensor Principal Component Analysis with Data Heterogeneity

统计数据增强及其在遥感图像智能解译中的应用

Conformal Robustness Control: A New Strategy for Robust Decision

Errors-in-Variables Gaussian Processes for Mixed-Input Regression

基于机器学习与联邦学习的2型糖尿病患病风险预测模型构建研究

Extreme Value-Informed Multi-Modal Transfer Learning for Blockchain Fraud Detection

FedFask: Fast Sketching Distributed PCA for Large-Scale Federated Data

Communication-Efficient Estimation for Non-Randomly Distributed and Missing Data

Deconfounding via Profiled Transfer Learning

Compression-Then-Aggregation of Local Risks for One-Shot Federated Learning

Conditional Generation via Diffusion, Flow, and Schrödinger Bridges

Asymptotic Theory in the AI Era

Causal Generalist Medical AI

Distributional Off-Policy Evaluation with Deep Quantile Process Regression

Semi-Supervised Conditional Diffusion Models

An Efficient Algorithm for Training LLMs with Constraints

Graph-based Multisample Comparison with Application to Feature Selection for Multi-Category Responses

Deep Sparse Masks via Optimal Transport

Kernel Ridge Regression with Predicted Feature Inputs and Applications to Factor-Based Nonparametric Regression

Selective Labeling with False Discovery Rate Control

Conditional Distribution Test via Flow Models

A Statistical Framework for Alignment with Biased AI Feedback

Inference of High-Dimensional Weak Instrumental Variable Regression Models without Ridge-Regularization

Optimal Multi-Machine Learning Assisted Semi-Supervised Inference

TBD

High-Dimensional Precision Matrix Quadratic Forms: Estimation Framework for p>n

Mean-Shift PCA by Knockoff Mean

Mesoscopic Dynamics in Complex Networks: A Random Matrix Perspective

Orthogonalized Kernel Debiased Machine Learning for Logistic Multimodal Inference

Simultaneously Leveraging Individual and Summary Level External Data in Clinical Trials

A Pharmacokinetics-Informed Bayesian Design for Dose Optimization in Multi-Regional Clinical Trials

数字孪生和个体处理疗效估计

贝叶斯适应性富集在中药研究的应用

A Joint Fairness Model with Applications to Risk Predictions for Underrepresented Populations

Optimizing Sample Size for Supervised Machine Learning with Bulk Transcriptomic Sequencing: A Learning Curve Approach

Learning Directed Acyclic Graph Models with Applications on High Throughput Omics Data

CausalGRN: Deciphering Causal Gene Regulatory Networks from Single-Cell CRISPR Screens

Conformal Prediction Beyond the Horizon: Distribution-Free Inference for Policy Evaluation

Bayesian Random Weight Neural Network Inference Engine

Deformed Q-learning for High-Dimensional Dynamic Treatment Regimes

Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting

Adaptive Transfer Clustering: A Unified Framework

Directed Hypergraph: Tensor Representation, Embedding Modeling, and Community Detection

Estimation and Statistical Inference for Generalized Multilayer Latent Space Model

A Manifold Learning Method for Noisy Independent Component Analysis

Robust and Efficient Estimation of Principal Causal Effects with Continuous Intermediates

Evaluating Surrogates in Individual Treatment Regimes

Long-Term Causal Inference under Persistent Confounding via Data Combination

Introducing the B-Value: Combining Unbiased and Biased Estimators from a Sensitivity Analysis Perspective

Randomization Inference with Sample Attrition

Design-Based Prediction-Powered Inference for Edge-Level Outcomes in Directed Networks

Principled Analysis of Crossover Designs: Causal Effects, Efficient Estimation, and Robust Inference

Relaxing Fisher's Sharp Null via Random Localization

低秩张量优化与半参高效统计推断及其在大模型评估中的应用

Statistical and Computational Limits for Cumulant Tensor Inference: A Regime in Which Efficient Detection is Harder Than Efficient Estimation

Optimal Convergence Analysis of DDPM for General Distributions

分布式差分隐私约束下的联邦主成分分析：最优收敛率与高效算法

High-Resolution Feature Identification in High-Dimensional Clustering

TBD

Community Detection in Heterogeneous Signed Networks

Bridging Theory and Practice: Statistical Inference for Latent Space Models of Networks

Scale-Free Correlation Change-Point Detection in High-Dimensional Dynamic Networks

Algorithm-Agnostic Post-Clustering Differential Expression Analysis with Asymptotic FDR Control

A Bayesian Transfer Learning Framework for Network Latent Space Models

Spectral Change Point Estimation for High Dimensional Time Series by Sparse Tensor Decomposition

A Cross-Layer Independent Cascade Model for Signaling Pathway Discovery: Uncovering the Dual Role of Ephx2 in Atherosclerosis

Upper-Tail Copula-Band Change Point Detection for High-Dimensional Time Series

利用汇总统计量进行因果效应异质性估计

Pathway-Guided Conditional Ultrahigh-Dimensional Feature Screening with Nested Group Structures for Survival Analysis

Population-Unbiased Calibration for High-Dimensional Logistic Regression with Measurement Error

Q-DREAM: Double Robust Estimation and Aggregation for High-Dimensional Quantile Mediation Analysis

Semiparametric Mixture Regression for Asynchronous Longitudinal Data Using Multivariate Functional Principal Component Analysis

Self-Supervised PET Analysis on Whole-Body Metabolic Networks in Cancer-Free Obesity

Addressing Non-Exchangeability in Hybrid Control Studies: A Variable Selection Approach

Statistical Tools for Integrative Proteogenomic Analysis

Stein-Encoder: A White-Box Supervised Encoder via Stein Identities

Enhancing Inference for Small Cohorts via Transfer Learning

Active Subsampling for Measurement-Constrained M-Estimation of Individualized Thresholds with High-Dimensional Data

Automatic Hybrid Neural ODE Reduction

Equivalence and Non-Inferiority Assessment in Clinical Trials by Win Probability

Testing Patterned Covariance Matrices Under Quadratic Subspace

Quantile Regression for Censored Data with A Cure Fraction

Semi-Parametric Estimation for Sample Selection Models

Prediction-Powered Linear Regression: A Balance Between Interpretation and Prediction

Distributed Privacy-Preserving Group Inference for High-Dimensional GLMs

Orthogonalized Score Tests for Conditional Variable Significance in Deep Partial Linear Cox Models

Maximum Likelihood Estimation in the Sparse Rasch Model

降维与表征——统计学与人工智能融通共进下的若干发展

Local Theory for the Adaptive Feature Program

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics

Impact of Membership Models on Subgroup Analysis

Research and Application of Sales Forecasting Based on Debiased Spatiotemporal Neural Networks

Transformer-Based Structural OHLC Price Forecasting for Chinese Agricultural Futures with Multi-Source Heterogeneous Data

经济系统数字孪生：从宏观经济治理视角

基于CNN-BiLSTM-MSHA模型融合投资者情绪的股价预测

共同富裕视域下黄河流域乡村产业振兴对农村人居环境碳排放的非线性效应及提升路径研究

Deep Isometric Manifold Embedding for Statistical Analysis of Financial Video Broadcasts

Adaptive Semi-Supervised Inference for Estimating Equations: A Nonparametric Projection Approach using ReQU Neural Networks

Deep Transformation Model

Dynamic Logistic Normal Multinomial Model for Microbiome Data

High-Resolution Inversion of Ocean Surface Current Fields via Diffusion Priors and Multimodal Constraints

Deep Nonparametric Quantile Regression under Covariate Shift

A Conditional Distribution Equality Testing Framework Using Deep Generative Learning

Generating Tensor Factor Structure with Diffusion Model via Tucker U-net

Extending VAEs to Discrete Latent Spaces

SADA: Safe and Adaptive Aggregation of Multiple Black-Box Predictions

An Interactive Learning Paradigm in the Age of Generative AI

Addressing Real-world Challenges in Cancer Early Detection Studies

Backdoor Reactivation with Clean Data

Matrix Harmonic Analysis at High Temperature

平面正交多项式和二维库伦气体模型

Absolute Continuity of Operator-Valued Random Variables

Operator Norm Bounds for Multi-Leg Matrix Tensors and Applications to Random Matrix Theory

Risk-Inclusive Contextual Bandits for Early Phase Clinical Trials

Distribution Theory of Random Projection Products

Design and Analysis of Two-Phase Medical Studies Using Model-Assisted Calibration Approaches

Non-Splitting Neyman-Pearson Classifiers

MOSAiC: A Unified Framework for Lossless, One-Shot, Federated Learning Algorithms

U-aggregation: Unsupervised Aggregation of Multiple Learning Algorithms

Bregman Information Projection for Calibration Estimation

Nonlinear Independent Component Analysis for Time Series via Invertible Neural Networks

When Does Synthetic Data Help Imbalanced Learning?

Signal-to-Noise Ratio Aware Minimax Analysis of Sparse Linear Regression

Belief in Dependence

Slacked Empirical Likelihoods for Post-Criterion Inference

TBD

Large Precision Matrix Estimation with Unknown Group Structure

Sequential Multiple Testing with Multiple Hypotheses and Prior Information on the Hypothesis Configuration

Multivariate Conformal Selection

Accounting for Network Noise in Graph-Guided Bayesian Modeling of High-Dimensional Omics Data

Forecasting of COVID-19 Incident Cases in Beijing Municipality Based on Hierarchical Forecasting Model

Sparse Multivariate Distribution-to-Distribution Regression via Dependent Mixtures -- A Bayesian Semiparametric Approach

Cross-Modal Brain Network Disruptions in Schizophrenia: Insights From Multiplex Modeling and Transcriptomic Associations

From Multi-Omics to Brain and Behavior: Statistical Integration of Exome Sequencing, Plasma Proteomics, and Neuroimaging in Mental Health Research

解析心脏结构与多维度大脑表型之间的共享遗传架构

Design and Analysis for Valid Causal Inference with Network-Dependent Data

Efficient Inference of Regional Treatment Effects in Multi-Regional Clinical Trials

Quadruply Robust Methods for Causal Mediation Analysis

Stabilized Debiased Machine Learning

Sparse Deep Integrative Latent Factor Regression for Supervised Multi-Modal Data Analysis

Balancing Utility and Cost in Dynamic Treatment Regimes

Prompt Perturbation for Reliable LLM Evaluation over Comparison Graphs

非线性矩阵补全在一般损失与采样分布下的最优性理论

PAC-Efficient Reasoning for Large Language Models: Marginal Guarantees, Conditional Extensions, and Anytime Validity

Robust Online Recommender System via Matrix Completion

分析师前瞻性对控股股东股权质押的影响——来自大语言模型的证据

A Compass for Useful Data: Online Data Selection via Alignment-Gated Fisher Geometry

High-Dimensional Center-Augmented Regularization for Simultaneous Subgroup Learning and Variable Selection

Feature Selection with Annealing for Shallow Neural Networks Using the Multi-Stage Stochastic Algorithm

REVS: A Reinforced Exploration Algorithm for Variable Selection via Thompson Sampling with UCB-Augmented Variance

An Improved Sufficient Condition for Weighted LR-L1 Minimization

Byzantine-Resilient Decentralized Optimization for Joint Feature Selection in Multi-Task Networks

Feature Splitting Parallel Algorithm for Dantzig Selectors

Joint Estimation of Edge Probabilities for Multi-Layer Networks via Neighborhood Smoothing

基于网络信息的近似因子模型估计

数据要素促进居民家庭服务消费的理论机制研究—基于CHFS的经验证据

Differentially Private Adaptive Neyman Allocation for Sequential Experiments

基本公共服务均衡布局能否增强城市创新网络韧性

Z-Valued Smooth Transition GARCH Models: Specification and Testing

A Unified Statistical Framework for Testing Stochastic Dominance

Testing and Estimation of Change Point in ARMA Model with Heavy-Tailed G-GARCH Noises

Impact Mechanism of Digital Economy Policies on the Synergistic Effects of Pollution-Carbon Reduction in Cities: A Causal Inference Approach Based on Double Machine Learning

Generalized Spectral Testing with Sample Splitting

Stable Causal Targeting with Machine Learning: Application to a Consumer Finance Field Experiment

伴有复发事件响应及不等随访时间的响应适应性随机化试验的样本量确定

基于高斯图模型的自适应多源先验融合正则化方法

The Randomized BH Procedure: A Framework Unifying Conformal and Competition Tests

A Greedy-Enhanced ABC-NS Framework for Epidemic Model Selection

A Bayesian Phase I/II Platform Design with Data Augmentation Accounting for Delayed Outcomes

Learning Overlapping Group Structures via Community Detection for High-Dimensional Variable Selection

On Ignorability of Preferential Sampling in Geostatistics

Spherically Embedded Time Series with Unknown Trend and Periodic Components

The Empirical Bayes Estimators of the Variance Parameter of the Normal Distribution with a Normal-Inverse-Gamma Prior Under Stein's Loss Function

二元Marshall-Olkin瑞利分布的参数估计

Statistical Inference for Coefficients and Trend Function in Time-Varying GARCH Model

Fisher Scoring for Exact Matérn Covariance Estimation through Stable Smoothness Optimization

Multi-Scale Dynamic Graph Neural Network for Electricity Load Forecasting

Hierarchically Sparse Neural Networks via Auxiliary Responses

Transfer Learning for Degree-Corrected Mixed Membership Network Models

An Adaptive Test for High-Dimensional Mean Change-Points

Closed-Loop Adaptive Monitoring and Fault Isolation for Partially Observed High-Dimensional Data Streams

SIRI: Tensor Rank Selection via Stability Index with Random Initializations

Aggregating Conformal Prediction Sets via α-Allocation

Beyond Two Arms: Power-Optimized Adaptive Experiments

Online Generalized Boundary False Discovery Rate Control under Arbitrary Dependence via Closure Principle

基于集成机器学习的祁连山草地全球变暖潜力预测

Graphical Regression with Shrinkage and Covariance Kernel

Tensor Decomposition-Based Neural Operator with Dynamic Mode Decomposition for Parameterized Time-Dependent Problems

Fast Fitting of Gaussian Mixture Model via Dimension Reduction

Inference in Dense High-Dimensional Heteroscedastic Regression

A New Approach to L0-Compressed Sensing with Finite-Step Oracle Convergence under the Sharp RIP Condition

Sparse Gaussianized Canonical Correlation Analysis with Applications to Portfolio Analysis

Semi‑Supervised Learning on Graphs with GNNs

Transfer Learning on Edge Connecting Probability Estimation Under Graphon Model

Fiedler Sign Consistency for Hierarchical Stochastic Block Models

Nuisance Parameter Tuning for Inference in Observational Studies

Feedback-Enhanced Online Multiple Testing with Applications to Conformal Selection

Conformalized Large-Scale Selective Inference with Informative and Trustworthy Prediction Sets

Conformal Selective Prediction with General Risk Control

Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle

基于混合数据学习半参数树模型

Minimax Optimal Robust Sparse Regression with Heavy-Tailed Designs: A Gradient-Based Approach

Poisson Subsampling-Based Estimation for Growing-Dimensional Expectile Regression Inmassive Data

网络下的高效实验设计与主动学习

Decentralized Robust Online Policy Evaluation

Doubly Robust Transfer Learning Under Sub-Group Shift for Cohort-Level Missing Indicator Covariates

中国统计学百年历史发展——从萌芽到崛起

洞见数据文明——中国统计学数字博物馆构想

薪火相传 笃行致远——上海财经大学统计学科史编撰成果

A Computationally Efficient Double-Group Binary Segmentation Method for Multiple Change-Point Detection

Complex Functional Data Analysis: From Separability to Weak/Partial Separability

Double Robust High Dimensional Alpha Test for Linear Factor Pricing Model

Changepoint Detection in Complex Models: Cross-Fitting Is Needed

Addressing Heterogeneity in High-Dimensional Regression through Bayesian Structured Sparse Clustering

Cox-MK: A Model-X Knockoff Method for Genome-Wide Survival Association Analysis

Prioritizing Druggable Targets by Mapping Human Disease-Associated Coding Variants onto Protein Structures

Joint High-Dimensional Inference for Mixed-Type Multi-Response Regression

A Novel Exact Confidence Interval for the Difference of Proportions in Paired Data Using a Restricted Most Probable Statistic

Efficient Genome-Wide Association Studies via Low-Rank Approximations

Variational Bayesian Estimation for Joint Models of Longitudinal and Interval-Censored Failure Time Data with Random Change-Points

Tensor-on-Vector Regression with Interactions with Application to FMRI Data

Statistical and Machine Learning Modelling of HLA-I Peptide Presentation Landscapes

Testing High-Dimensional Mediation Effect with Arbitrary Exposure–Mediator Coefficients

Hilbert Diffusion Models for Generating Functional Data with Galerkin-Type Kernel Neural Operators

Deep Symbolic Learning for Histogram-Valued Regression Data

From Binary Pairs to Soft Correspondences in Audio Text Retrieval

Information Matrix Test for Normality of Innovations in Stationary Time Series Models

Exploiting Training Dynamics for Anomaly Detection in Deep Generative Models

An Association Measure for Mixed-Types Variables

Bayesian Sufficient Dimension Reduction via Envelope Models

Hilbertian Additive Regression with General Estimated Variables

Statistical Inference for Latent Space Models of Network Data with Edge Covariates

Non-Asymptotic Gaussian Approximation for Two-Timescale Stochastic Approximation

Causal Mediation Analysis with Partially Observed Mediators

Towards Robust Machine Learning under Imperfect Data

Synergy Evaluation for Drug Combinations: From Classical Concepts to Model-Based Approaches

Bayesian Borrowing in Confirmatory Trials: Priors, Performance, and Implementation in Practice

AI-Powered Digital & Intelligent Platforms in Pharmaceuticals with Key Considerations

Application of Adaptive Phase II/III Seamless Designs for Dose Selection: A Comparative Study of Inferentially and Operationally Seamless Designs

Estimating All-Terminal Signature for Networks by Using Deep Neural Learning

Modeling Multivariate Degradation with Time-Varying Mean–Variance Dynamics for Reliability Assessment

RUL Prediction for Aircraft Engines by Integrating Nonlinear Functional Data Analysis and Graph Attention Network

CADA-Flow: Capturing Complex Dependence in Cyber Breach Risk via Deep Learning

Interpretable Causal Mediation Analysis with Graph Autoencoders

Power Enhancing Probability Subsampling Using Side Information

Type-Preserving Differentially Private Data Release for Versatile Analysis of Mixed-Type Data

Online Robust Locally Differentially Private Learning for Nonparametric Regression

从聚合型多样性到结构权变贡献：基于图学习解析团队异质知识的整合机制

极小极大最优的在线非平稳强化学习

基于船测丰度约束的海底地形深度构建方法

A Nudging-Based Multigrid Ocean Data Assimilation System in North Pacific

Asymptotic Theory for Generalized Total Least Square for Optimal Fingerprint Estimation in Climate Change Studies with Non-Gaussian Errors

A Real-Time Protection Procedure for Computerized Adaptive Testing Under Item Preknowledge via Online Bayesian Changepoint Detection

局部散度惩罚与多专家混合 e-过程：分布自由序贯变点检验的鲁棒方法

探究城市活力与建成环境的关联机制：多源数据驱动的非线性特征与阈值效应研究

Detecting Multiple Changepoints in the Annual Number of Snowy Weeks via Latent Gaussian Beta-Binomial Modeling and Pairwise Likelihood

Identifying the Dynamic Spreading Mechanism of Livestock Infectious Diseases Using Multivariate Hawkes Processes

融合双域变换的地震数据低秩恢复方法

Identifying Chinese Leading Venture Capital Firms Using Investing Preference-Enhanced Graph Neural Networks

A Multiple Changepoint Detection Method for Examinee Aberrant Behaviors Based on Bootstrap Intensity Scores and Weighted Binary Segmentation

Fit First and Detect Later: A Unified Decoupled Framework for Change Detection in High Dimensions

Fair Regression in Reproducing Kernel Hilbert Spaces: Single-Machine and Decentralized Implementations under Conditional Mean Parity

Data-Driven Policy Learning for Continuous Treatments

Statistical Inference for Mediation Models with High Dimensional Exposures

Generalized Transfer Learning based on Mallows Model Averaging

Dynamic Mean-Variance Problem with Frictions

Stochastic Reaction-Diffusion Equations with Super-Linear Drift

Joint Law Limits for Non-Autonomous Multi-Scale Diffusions with Irregular Coefficients

Stochastic Wave Equation with Additive Fractional Noise: Solvability and Global Hölder Continuity

Towards Central Limit Theorem of Critical Branching Random Walks

二维高斯自由场的臂概率

Branching Random Walks and Percolation on Hyperbolic Groups

TBD

Invariance Learning from Heterogeneous Environments via Neural Networks

Making Algorithms Robust to Structured Noise and Beyond

Whom to Query for What: Adaptive Group Elicitation via Multi-Turn LLM Interactions

The Optimal Selection of a Subset and the Roles of Testing

A Nonparametric Potential Outcomes Framework for Bidirectional Causal Inference

Score Test for Order of Finite Normal Mixtures

From Graph-Based Tests to Graph-Induced Ranks: Two-Sample Inference for Complex Data

Limit Theorems of Azadkia-Chatterjee’s Conditional Graph Correlation

TBD

Randomized Optimal Switching Problem and Related Mirror Descent Flow

Sequential Propagation of Chaos for Mean-Field BSDE Systems

The Deep Truncated FBSDE Method: A Robust Solver for High-Dimensional PDEs

Comparison Theorems for Mean-Field BSDEs Whose Generators Depend on The Law of The Solution (Y,Z)

Doubly BSDE and SPDE with Quadratic Growth

Mean Reflected Backward Stochastic Differential Equations

超前信息的随机控制

Quadratic Forward Backward Stochastic Differential Equations Driven by G-Brownian Motion

Two-Time-Scale McKean-Vlasov Systems

Mean Field Control with Poissonian Common Noise: A Pathwise Compactification Approach

Controlled Particle Systems and Their Applications in Deep Learning

Bi-Coupling Approach and its Applications

数据驱动方法在三维海洋信息重构中的应用

Statistics-Assisted Ocean Observing: Designing, Guiding, and Reconstructing Mesoscale Eddy

TBD

Non-Identifiability of Proxy-Based AMOC Early-Warning Signals under Red Noise

Rank Deficiency of Bernoulli Random Matrices for Large k

Rates of Convergence in the Distances of Kolmogorov and Wasserstein for Standardized Martingales

Refined Berry-Esseen Bounds under Local Dependence

High-Dimensional Normal Approximations for Sums of Langevin Markov Chains

TBD

TBD

Spectral Analysis of Sample Covariance Matrices under Kronecker-Sum Precision Structures

TBD