Physics-informed learning and uncertainty quantification

Causal Inference : History, Contributions, and Future

Robust Consensus Learning with Multi-Institutional EHR Data: Opportunities and Challenges

Causal Inference with Negative Controls when many negative control exposures exist

Imputation-Based Randomization Tests for Randomized Experiments with Interference

Efficient Design-based Inference for the Stepped Wedge Design

Identification and estimation of causal peer effects using instrumental variables

A generalized tetrad constraint for nonlinear models

When can weak latent factors be statistically inferred?

Counting Cycles with AI

A new spectral approach to dynamic network analysis

Optimal Experimental Design for Neighborhood-Based Network Regression

A Bayesian Approach for Fine-Tuning Diffusion Models

Provable Diffusion Posterior Sampling for Bayesian Inversion

To Intrinsic Dimension and Beyond: Efficient Sampling in Diffusion Models

A Generative Embedding Approach for Hypergraphs

Full-conformal novelty detection: A powerful and non-random approach

Structured E-Value Filter for Set-Wise Inference, with Applications to Brain Imaging Studies

Selective Randomization Inference for Adaptive Experiments

Optimal Model Selection for Conformalized Robust Optimization

Robust subsampling via low influence functions in contaminated data

Efficient Multilevel Joint Modeling: Integrating Longitudinal and Survival Data with Auxiliary Poisson Approach

Information Transfer Enhancing the Functional Regression

Quantile regression for censored data with a cure fraction

TBD

Parameter-transfer in spatial autoregressive models via model averaging

A Gaussian Algorithmic Stability Framework for Post-Selection Inference

Model-free feature screening for ultrahigh-dimensional classification data

Statistical Approaches to MLP Approximation in Efficient Language Models

Advancing Responsible Statistical and AI/ML Methods for Complex Electronic Health Records

Generalized Median of Means Principle for Bayesian Inference

Net analysis in Chinese city production

Research on Theoretical and Methodological Approaches for Statistical Analysis of Economic Complex System Networks

The Evolution of China's Logistics Cost Footprint Spatial Network and Analysis of Influencing Factors

Research on the Measurement and Network Structure of China's Logistics Industry in the Context of Dual Circulation

Mixture Survival Trees for Subgroup Discovery

Auxiliary Variable-Assisted Regularized Estimation: Semi-Supervised Modeling with Multi-Wave Sampling

Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations

Dynamic Classification of Latent Disease Progression with Auxiliary Surrogate Labels

Two-way latent matching model for network analysis

A dynamic network autoregressive model for time-varying network-link data

A Semiparametric Regression Model for Spatiotemporal Processes with Nonseparable Covariance Structures

Change point detection for tensor data with low-rank and sparse structure

Learning with Shared Representations: Statistical Rates and Optimal Algorithms

Optimal Variable Clustering for High-Dimensional Matrix Valued Data

Distributional learning via deep copula density weighting

Supporting Evidences for the Adaptive Feature Approach

Learning guarantee of reward modeling using deep neural networks

Model Free Prediction with Uncertainty Assessment

Wasserstein Distributionally Robust Nonparametric Regression

Rates for least squares using over-parameterized neural networks

Support vector machines with probabilistic linguistic information

Clustering Analysis of Text Interval Functional Data Based on the BERT Model: A Case Study of Live Stream Chat Messages

Research on Group Consensus Evaluation Model Considering Non-cooperative Behavior in Dynamic Social Network Environments

公共数据产品定价和利润分配的非合作-合作两型博弈方法

Attribute preference weight estimation method of commodity evaluation based on online reviews and ratings

MOSAICA with application to global factor investment

Change surface regression for nonlinear subgroup identification

TBD

A General Latent Embedding Approach for Modeling Non-uniform High-dimensional Sparse Hypergraphs with Multiplicity

Non-Euclidean object filtering for large-scale discriminant analysis

Heavy-Tailed Density Estimation

Efficient methods for species tree estimation and species delimitation using genomic sequence data

Range Penalization: Theoretical Insights with Applications in Federated Learning

A Generalized Integration Approach to Association Analysis’, focusing on epi side of tumor association analysis

Evidence-based practice for Epi-transcriptomic data harmonization

Integrative multi-omics analysis elucidates molecular links underlying genetic effects on complex traits

Learning ligands and receptors networks using directed acyclic graphical models with mixed variables

Modeling Emotional Expressions for Multiple Cancers via a Linguistic Analysis of an Online Health Community

Stage-Aware Learning for Dynamic Treatments

Multi-Objective Optimization for Causal Learning of Tolerant Dynamic Treatment Decision Rules

Robust transfer learning for individualized treatment rules in the presence of missing data

Conformal prediction after efficiency-oriented model selection

Improve Fairness with Shift-Adjusted Neyman--Pearson Classifiers via Single Index Modeling (SACSI)

Statistical analysis of 3D path data in Minecraft

Investigating Causal Effects of Wearable Device Usage in Diabetes Management

CTE2: Conditional tail expectation treatment effect at extreme levels

Mean-preserving rounding integer-valued ARMA models

基于广义线性模型的大规模插补样本融合研究

基于投影经验过程的渐近分布自由的超高维回归模型检验

基于超均匀性的差分隐私多重假设检验

Heterogeneous Quantile Treatment Effect Estimation with High-Dimensional Confounding

Generalized quantile regression for recurrent event data with covariate measurement error

Statistical Inference for High-dimensional Linear Regression Based on Feature Transfer Learning

Sample Efficient Nonparametric Regression via Low-Rank Regularization

Mean shift for functional data: a scalable algorithm and convergence analysis

Bivariate Analysis of Distribution Functions Under Biased Sampling

Coordinate testing for general sufficient dimension reduction methods

Graphical modeling of multivariate inhomogeneous spatial point processes

Exploring the relationship between the geometry of a fixed embedding of image data and its underlying cluster structure

Statistical Generative Models for Unstructured Image Data

D-CDLF: Decomposition of Common and Distinctive Latent Factors for Multi-view High-dimensional Data

Doubly robust alignment for large language models

带协变量缺失的高维线性回归

Nonparametric Sensitivity Analysis for Unobserved Confounding with Survival Outcomes

基于缺失患者报告结局数据的亚组治疗效应检测

Transition and dynamic reconfiguration in late-life depression based on hidden Markov model

Assessing Global Border Controls as Responses to Pandemic Using Real-World Data and Target Trial Emulation

A Modified Normalized Power Prior Approach for Bayesian Adaptive Borrowing in Item Response Theory Models

Transformation Screening

Structure Identification and Learning for Ultra-High-Dimensional Generalized Partially Linear Spatially Varying Coefficient Models

Unveiling Genetic Complexity: Fine Mapping with h2-D2 Bayesian Approach in Multi-Ancestry Settings

Bayesian empirical likelihood procedure for evaluating racial disproportionality of policing Stop & Search in London

Distributional Regression & Uncertainty Quantification with Deep Learning

Uncertainty Learning for Portfolio Optimization on Big Data

A Risk Model with Stochastic Quadratic Intensity

Distributionally Robust Optimization against Ambiguity across Two Layers

Transfer Learning for Benignly Overfitted Minimum Norm Interpolator

Adaptation and Generalization in High-Dimensional Ising Models Using Transfer Learning

Iterative Nuclear Norm Minimization for Parameter Estimation in High-Dimensional Multiple Response Models

Geodesic Causal Inference

Interpretable Personalized Online Reinforcement Learning with Applications in Business and Healthcare

Privacy-Preserving Transfer Learning for Community Detection in Multiple Networks

The synthetic instrument: From sparse association to sparse causation

On the Particle Approximation of Lagged Feynman-Kac Formulae

Financial forecasting with voice time series data

Approximate Bayesian computation methods for complex data

Generative or Discriminative? Rethinking Image Generation under Complex Conditions

Local genetic correlation via knockoffs reduces confounding due to cross-trait assortative mating

MultiSTAAR: a powerful multi-trait rare variant analysis framework for biobank sequencing data

Individualized dynamic latent factor model with application in mobile health data

Deciphering proteins in Alzheimer’s disease: A new Mendelian randomization method integrated with AlphaFold3 for 3D structure prediction

Heritability estimation with similarity representation

Individualized Inference for Causal Fairness through Conformal Mediation Analysis

Deep Orthogonal Learner for Conditional Quantile Treatment Effect Estimation

Heterogeneous Quantile Treatment Effect Estimation for Longitudinal Data with High-Dimensional Confounding

Rerandomization for covariate balance mitigates $p$-hacking in regression adjustment

Chang-Point Detection in Network Vector Autoregressive Models

Matrix Factor Model with Structural Breaks

Two-way Homogeneity Pursuit for Quantile Network Vector Autoregression

Matrix Time Series Modeling: A Hybrid Framework Combining Autoregression and Common Factors

Exponentially Tilted Empirical Likelihood Inference for Quantile-GARCH Models

On smooth transition interval autoregressive models

Semiparametric marginal promotion time cure model for clustered survival data

Fast Multinomial Logistic Regression with Group Sparsity

Approximation Error from Discretizations and Its Applications

Testing For Heterogeneity in Distributed Statistical Learning

OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction

Factor-Assisted Federated Learning for Personalized Optimization with Heterogeneous Data

Federated Learning based on Kernel Local Differential Privacy and Low Gradient Sampling

Quantile regression for a decentralized distributed system

Matrix-factor-augmented regression

Robust matrix auto-regressions and digital finance analysis in Yangtze River Economic Belt

Anomaly or Risk Factor? A Stepwise Evaluation

Factor-augmented Convolution Smoothed Quantile Regression

Beyond the Surface: Advanced Estimation of Ocean Interior Velocities via Surface Observations

融合多源信息的TimeGPT-GARCH族金融市场波动率预测模型

A further review on the optimal fingerprinting approach for climate studies, the case of errors in fingerprints

Partial Functional Dynamic Structural Equation Model

Sparse Boosting for Additive Spatial Autoregressive Model with High Dimensionality

Learning individualized treatment rules for a target population with right-censored survival outcomes

Efficient Risk Assessment of Time-to-Event Targets With Adaptive Information Transfer

Semiparametric Bayesian regularized quantile regression to mixed effect model for health insurance data

MM-LSNet: A Multi-Level Multi-Task Framework for Laser Spot Analysis in UWF-OCTA Images

Transfer learning for accelerated failure time model with microarray data

Multiple Change-point Detection for High-dimensional Functional Time Series

A Unified Principal Components Analysis for Stationary Functional Time Series

Random Fourier Features Based Gaussian Process Models for Stochastic Simulations

Statistical Inference for Community Detection in Dynamic Networks

A Conformalized Empirical Bayes Method for Multiple Testing with Side Information

A Multi-Method Integration Framework for Wind Speed Prediction Using Optimized Deep Neural Networks

Defense Against Syntactic Textual Backdoor Attacks with Token Substitution

e-GAI: e-value-based Generalized α-Investing for Online False Discovery Rate Control

Locally Private Nonparametric Contextual Multi-armed Bandits with Transfer Learning

The Promises of Multiple Experiments: Identifying Joint Distribution of Potential Outcomes

Hyperspectral and Multispectral Image fusion with Functional Data Analysis Techniques

Ordering factorial designs with good stratification properties

Group SLOPE Penalized Low-Rank Tensor Regression

Functional Dependence of Network Data: An Approach without Metric Space

Network Assisted Approximate Factor Model Estimation

Estimation of a Spatial Autoregressive Model with Endogenous Group Formation

Network Cross-Validation for Nested Models by Edge-Splitting

Towards an understanding of the principles behind deep learning

Statistics in the Era of Large Models

Generative AI for Economic Equilibrium Analyses and Financial Applications

Strategies and Best Practices in Academic Writing

Doubly Robust Sequential Quantile Off-Policy Inference

Non-greedy Tree-based Learning for Estimating Global Optimal Dynamic Decision Rules With Continuous Treatment Dosage

Causal Inference for all: Marginal causal effects for all outcomes truncated by death

Minimax Detection Boundary and Sharp Optimal Test for Gaussian Graphical Model

Partial penalized quasi-likelihood with covariance matrix misspecification

A Robust Combination Test Based on EDF Statistics for Goodness-of-Fit

Covariate-Adjusted Generalized Factor Analysis with Application to Testing Fairness

Pseudo-Likelihood Ratio Screening based on Network Data with Applications

BASIC: Bipartite Assisted Spectral-clustering for Identifying Communities in Large-scale Networks

Nonparametric learning of heterogeneous graphical model on network-linked data

A preferential latent space model for text networks

Causal Invariance Learning via Efficient Optimization of a Nonconvex Objective

When Few Labeled Target Data Suffices: A Theory of Semi-Supervised Domain Adaptation (SSDA)

A Unified Framework for Large-Scale Classification: Error Rate Control and Optimality

Robust Reinforcement Learning under Diffusion Models for Data with Jumps

Robust Rank Canonical Correlation Analysis for Multivariate Survival Data

Estimation of Multiple Large Precision Matrices and Its Application to High-Dimensional Quadratic Discriminant Analysis

Adaptive Block-Based Change-Point Detection for Sparse Spatially Clustered Data with Applications in Remote Sensing Imaging

Semiparametric sieve estimation for survival data with two-layer censoring

Understanding the Effects of Arousal in Online Reviews on Product Demand from New Versus Returning Customers

Profile GMM estimation of dynamic spatial panels with multidimensional endogeneity and interactive fixed effects

Bridging Factor and Sparse Models in Time-varying Environments

Learning the Stochastic Discount Factor

Neural Tangent Kernel in Implied Volatility Forecasting: A Nonlinear Functional Autoregression Approach

Let the tables talk!

Learning Volatility Roughness from Options

Exploring the Heterogeneity in Recurrent Episode Lengths Based On Quantile Regression

A Scalable Distribution-Free Test for Detecting Spatially Variable Genes in Large-Scale Spatial Transcriptomics

Imputation-based Q-learning with regression trees for censored survival data

Kernel-Profile Efficient Estimation in Generalized Partially Linear Models With Missing Outcomes in Longitudinal Studies

Strategies and Insights for Successful Grant Applications

Sparse sample-specific matrix factor regression for interpretable phenotype prediction in scRNA-seq data

EpiRiskNet: incorporating graph structure and static data as prior knowledge for improved time-series forecasting

两异质人群背景下基于迁移学习的孟德尔随机化方法

基于时间尺度的动态预测模型——应用到阿尔茨海默病病程进展

Goodness-of-fit tests in functional-coefficient autoregressive models with measurement error

A Unified Framework of Analyzing Missing Data and Variable Selection using Regularized Likelihood

A Debiased Approach to Sparse Function-on-Scalar Regression with Covariate Measurement Error

Theoretical Guarantees for Alternative Least Square Algorithm in Tensor CP Decomposition

Statistical Inference for Low-Rank Tensor Models

Robust and Optimal Tensor Estimation via Robust Gradient Descent

Robust Matrix Estimation with Kronecker Product Structures via Scaled Projected Gradient Descent

Privacy Introduces Minor Trade-Offs in Fine-Tuning: A Representation Learning Perspective

Generalizability through the Lens of Distributional Learning

Multi-source stable variable importance measure via adversarial machine

Sparsity-Induced Global Matrix Autoregressive Model with Auxiliary Network Data

Convergence and Inference of Stream SGD, with Applications to Queueing Systems and Inventory Control

Fourier dimension of the graph of fractional Brownian motion with H>1/2

Convolution Bounds on Quantile Aggregation

Maximum Entropy Estimator for Hidden Markov Models

器械真实世界研究作为产品上市支持性证据的统计学考量

混合设计和贝叶斯统计支持监管决策案例分享

脑电数据的自动标记与统计分析

Win Ratio方法及其在医疗器械试验中的应用

Discussant

Drawing inference from predicted data

Functional principal component analysis with informative observation times

Accurate Inference for Penalized Logistic Regression

Regret Minimization and Statistical Inference in Online Decision Making with High-dimensional Covariates

Inference on Potentially Identified Subgroups in Clinical Trials

A Longitudinal Multi-Domain Latent Structure Model for Domain-specific Disease Progression

Distributed Proportional Likelihood Ratio Model with Application to Data Integration Across Clinical Sites

Deep Mutual Density Ratio Estimation with Bregman Divergence and its Applications

How Digital Economy Promotes Rural Revitalization: The Road to Transform the County Industrial Structure under Rural E-commerce Policies

How Valuable are Chinese Patents?——An Innovative Measurement Distinguishing Private Value and Social Value

Real-time Monitoring of Economic Climate Based on High-dimensional Multisource Data

Understanding Neural Network Training: A Dynamical Stability Perspective

Accelerating Convergence in Bayesian Few-Shot Classification

基于SLeM框架的学习率自设定方法

矩阵信息论视角下的表征学习

共同富裕促进代际收入流动吗——基于微观家庭数据的经验研究

AI智能体能否成为智能投顾新助手

数据要素市场化配置对企业新质生产力的影响研究 ——基于A股上市公司的经验证据

基于协变量自适应随机化的多重政策分位数处理效应模型及其应用

High-dimensional graphical inference via partially penalised regression

Time-lagged marginal expected shortfall

Bayesian Grouping-Gibbs Sampling Estimation of High-dimensional Linear Model with Non-sparsity

Group Sparse $\beta$-Model: Multi-Magnitude Core Node Influence

Robust Model Averaging Prediction of Longitudinal Response with Ultrahigh-dimensional Covariates

MAP: Multi-Human-Value Alignment Palette for Safe and Personalized Generative AI

Adversarial Learning for Nonparametric Regression: Minimax Rate and Adaptive Estimation

Greedy Algorithms for High-Dimensional Generalized Linear UnderCovariate Shift

Efficient and accurate additive regression for high-dimensional data

Statistical Inference for Topological Data Analysis

Reduced varying coefficients of regional quantile for multiple responses

Joint estimation of monotone curves via functional principal component analysis

Grouped Orthogonal Arrays

混合水平强正交表的构造及其应用

Multi-resolution subsampling for linear classification with massive data

Theory of J-characteristics of four-level designs under quaternary codes

Deterministic Construction Methods for Uniform Designs

A Stratified L_2-Discrepancy with Application to Space-Filling Designs

Design of Order-of-Addition Two-Level Factorial Experiments

Recent works on absolute discrepancy in uniform designs

Fundamental Bias in Inverting Random Sampling Matrices with Application to Sub-sampled Newton

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

Random k conditional nearest neighbor for high-dimensional data

Optimal and exact recovery on general non-uniform Hypergraph Stochastic Block Model

Deep batch learning in high-dimensional nonparametric contextual bandits

Moment-integrated Bias-adjusted Spectral Method for Community Detection in Multi-layer Networks

Valid Inference for Clustering via Algorithmic Stability

Composite Kernel Two-Sample Tests

Expectation Identity of the Negative Binomial Distribution and Its Application in the Calculations of High-Order Origin Moments

Safe, Always-Valid Alpha-Investing Rules For Doubly Sequential Online Inference

Subsampling Based Inference for Large Networks

数据结合--网络数据指导下的高维特征最优选取方法

UBSea: A unified community detection framework

Exact Minimax Optimality of Spectral Methods in Phase Synchronization and Orthogonal Group Synchronization

Physics-informed Statistical Data Fusion for Reconstructing Current Fields of An Oceanic Eddy

Semi-supervised multiple testing with weighted false discovery rate control

A Generalized Framework for Approximate Co-Sufficient Sampling

A joint model for graded responses and response times

Generalized Independence Test for Modern Data

Statistical inference of spatial heterogeneity regression models

Estimation and Inference of Spatial Autoregressive Model under Complex Network Structure

Robust Estimation for Dynamic Spatial Autoregression Models with Nearly Optimal Rates

Double Robust Estimation for mixed linear effects models

Estimation of Treatment Effects based on Kernel Matching

Significance Testing for index in Varying Coefficient models

Stylized facts of metaverse non-fungible tokens

Minimax Optimal Design with Spillover and Carryover Effects

Mixed-input Gaussian Process Regression: An Errors-in-variables Approach

Multi-relational Network Autoregression Model with Latent Group Structures

Intersubject functional variability of gray and white matter in autism spectrum disorder

Designing Trials with Multiple Objectives using Graphical Approach for Multiple Scenarios

Compound Poisson mixed models for subject-specific multivariate data with left censoring

基于相似性动态利用多个真实世界数据源进行疗效估计

Double Optimal Transport for Differential Gene Regulatory Network Inference with Unpaired Samples

Detecting Food Adulteration Using chemical test and Graph-based Semi Supervised Framework

Exploring Heavy-Tailed Data in EDA: Visualization Strategies with R Package DeepWater

保形预测框架下的心电去噪对抗生成与因果推断的整合

Regime-specific Return Predictability in Quantiles

运用人工智能大语言模型技术构建基于空间转录组数据的计算细胞模型

Renewable prediction of model averaging in the Cox proportional hazards model with streaming data

基于随机效应模型对全球多中心临床试验的一致性评价和区域样本量计算

GWM-HFN：一种用于功能连接组的新型灰白质异构融合网络

Using Model-Assisted Calibration Methods to Improve Efficiency of Regression Analyses by Integrating Multiple Data Sources

On P-value Combination Procedures

Bayesian Integrative Region Segmentation in Spatially Resolved Transcriptomic Studies

Mitigating Bias in Analyzing Privacy-Preserved Survival Data

PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders

A spatial-correlated multitask linear mixed-effects model for imaging genetics

Robust Subgroup Analysis under Rank Regression

Identifying Cellular Niches in Spatial Transcriptomics: An Investigation into the Capabilities of Large Language Models

细胞通讯网络的统计推断

Disentangling single-cell perturbation responses with causality-aware generative model

scPLAN: a hierarchical computational framework for single transcriptomics data annotation, integration and cell-type label refinement

Covariate-adaptive design: An overview and recent advances

Optimal Treatment Allocation for Efficient Policy Evaluation in Sequential Decision Making

Dynamic Subgroup Identification in Covariate-adjusted Response-adaptive Randomization Experiments

测试

Normal-Reference Tests for High-Dimensional Hypothesis Testing

SOFARI-R: High-Dimensional Manifold-Based Inference for Latent Responses

Local Information for Global Network Estimation in Latent Space Models

Inference for possibly misspecified generalized linear models with non-polynomial dimensional nuisance parameters

Trustworthy assessment of heterogeneous treatment effect estimator via analysis of relative error

Semiparammetric M-estimation with Overparameterized Neural Networks

LAMBDA: A Large Model Based Data Agent

p=N^2 Assures Optimality

The Impact of Unobserved covariates on Covariate Adaptive Randomized Experiments

Sequential Monitoring of Covariate Adaptive Randomized Clinical Trials with Nonparametric Approaches

Statistical Inference with Mixed-Effect Model for Covariate-Adaptive Randomized Experiments

Addressing model uncertainty in treatment effect estimation under covariate-adaptive randomization: a cross-validated model averaging approach

Optimal Assortment and Pricing Via Generalized MNL Models with Novel Poisson Arrivals

Regularizing BELIEF with Sequency Lasso

Equity Network: Government Ownership in Business Groups

Interpretable Factors of Firm Characteristics

Analysis of Competing Risks Data with Censored Covariates

SurGAN: A Generative Adversarial Network Model for Tabular Survival Data

Variable Selection in Partially Functional Accelerated Failure Time Model

Estimation and Variable Selection for Interval-censored Failure Time Data with Random Change Point and Application to Breast Cancer Study

Semiparametric single-index structural equation model

Adaptive adequacy testing of high-dimensional factor-augmented regression model

A Robust Covariate-Balancing Method for Estimating Individualized Treatment with Censored Data

Homogeneity Pursuit in Ranking Inferences based on Pairwise Comparison Data

AI4Science and Science4AI

Toward Gene Language Model via Multi-omics Data

A unified framework for identification of cell type-specific spatially variable genes in spatial transcriptomic studies

Towards AI Virtual Cells through Dynamical Generative Models

Distributional Off-Policy Evaluation with Deep Quantile Process Regression

Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator

Theoretical Modeling of LLM Self-Improvement Training Dynamics Through Solver-Verifier Gap

A Statistical Hypothesis Testing Framework for Data Misappropriation Detection in Large Language Models

Denoising Diffusions with Optimal Transport: Localization, Curvature, and Multi-Scale Complexity

Do Large Language Models Need Statistical Foundations?

Model-assisted and Knowledge-guided Transfer Regression for the Underrepresented Population

New Evidence for the Predictive Role of Covariate Shift in Treatment Effect Generalization

Distributionally robust risk evaluation with an isotonic constraint

A New and Efficient Debiased Estimation of General Treatment Models by Balanced Neural Networks Weighting

Model-free high-dimensional knockoff inference with privacy constraints

Data-Utilization at the Core: A Unified Conformalized Multiple Testing Framework

Boosting In-Context Learning in LLMs Through the Lens of Classical Supervised Learning

Latent Noise Injection for Private and Statistically Aligned Synthetic Data Generation

Inference under Treatment Misclassification in Real-World COVID-19 Vaccine Effectiveness Studies

Antithetic Noise in Diffusion Models

A Reinforcement Learning Framework for Learning Optimal Oxygen Treatments in Patients with Acute Respiratory Distress Syndrome

Radial Neighbors for Provably Accurate Scalable Approximations of Gaussian Processes

BACT: nonparametric Bayesian cell typing for single-cell spatial transcriptomics data

Variational bagging: a robust approach for Bayesian uncertainty quantification

Dependency-aware deep generative models for multitasking analysis of spatial omics data

Error-controlled interaction discovery in generic machine learning models

Sparse Learning for Assessing the Association Between Gut Microbiome and Parkinson’s Disease

A new phylogeny-aware microbiome data generator

Representation Learning for Drug-Target Interaction Prediction

OPERA: An Interpretable Algorithm for Patient Stratification based on Partially Ordered Risk Factors

BELIEF in Dependence: Leveraging Atomic Linearity in Data Bits for Rethinking Generalized Linear Models

Scalable Manifold Learning for Complex Imaging Data Analysis

A foundation model for generalizable cancer diagnosis and survival prediction from histopathological images

Coarse-grained Hawkes processes

Bayesian inference of spatiotemporal Hawkes processes with Gaussian-process Priors

Likelihood-Free Estimation of Hawkes Processes from Binned Count Data

Latent Network Structure Learning From High-Dimensional Multivariate Point Processes

PEARL: Performance-enhanced Aggregated Representation Learning

Optimal Multi-Machine Learning Assisted Semi-Supervised Inference

Handling model uncertainty in the EM algorithm by model averaging

Prediction-Powered Prediction

Deep nonparametric approaches to domain generalization

Word-Level Maximum Mean Discrepancy Regularization for Word Embedding

Sparse representation learning for scalable single-cell RNA sequencing data analysis

Interpretable Deep Regression Models with Interval-Censored Failure Time Data

Adaptive Testing and Estimation for High-Dimensional Covariance Change-Points

TARGET INFERENCE FOR HIGH-DIMENSIONAL QUANTILE REGRESSION

False Discovery Rate Control Via Bi-Gaussian Mirrors

Functional data analysis via neural networks

High-Dimensional Bias Propagation in Multi-Temporal Covariance Dynamics: A Random Matrix Theory Approach