理论 · statistics论文趋势 2023–2026

主要结论

• 理论 · statistics论文从 2023 年的 16 篇增长到 2026 年的 57 篇，三年间扩大到约 3.6 倍。
• NeurIPS 是发理论 · statistics论文最多的会议，2023–2026 年共 58 篇，占四个会议总量的 42%。
• 交叉方向里涨得最快的是理论 · learning theory：同时属于两个主题的论文从 2023 年的 1 篇增至 2026 年的 28 篇。
• 在「理论与统计」的 5 个主题里，它的 2026 年论文数排第 5；同组增长最快的理论 · learning theory是 5.6 倍，理论 · statistics是 3.6 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026Asymptotic Anytime-Valid Inference for U-statistics
• ICML 2026A Theory of How Pretraining Shapes Inductive Bias in Fine-Tuning
• ICLR 2026The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics
• NeurIPS 2025A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
• ICML 2025Contextual Bandits for Unbounded Context Distributions
• ICLR 2025Improving Pretraining Data Using Perplexity Correlations
• CVPR 2025Dynamic Group Normalization: Spatio-Temporal Adaptation to Evolving Data Statistics
• NeurIPS 2024FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
• ICML 2024Neural Networks Learn Statistics of Increasing Complexity
• ICLR 2024Kernelised Normalising Flows
• NeurIPS 2023Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics
• ICML 2023Fair Densities via Boosting the Sufficient Statistics of Exponential Families
• ICLR 2023Don’t fear the unlabelled: safe semi-supervised learning via debiasing
• NeurIPS 2026Computationally sufficient statistics for Ising models
• ICML 2026Adaptive Multiscale Binary Expansion Tests for Independence
• ICLR 2026Bayesian Influence Functions for Hessian-Free Data Attribution
• NeurIPS 2025Backward Conformal Prediction
• ICML 2025Eigen Analysis of Conjugate Kernel and Neural Tangent Kernel
• ICLR 2025From Risk to Uncertainty: Generating Predictive Uncertainty Measures via Bayesian Estimation
• NeurIPS 2024Statistical Multicriteria Benchmarking via the GSD-Front

全部理论 · statistics论文

共 138 篇，第 3 / 3 页

101. NeurIPS 2025Tight Asymptotics of Extreme Order Statistics
102. ICLR 2024A Lightweight Method for Tackling Unknown Participation Statistics in Federated Averaging
103. ICLR 2024Kernelised Normalising Flows
104. ICML 2024DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric Estimation
105. ICML 2024Neural Networks Learn Statistics of Increasing Complexity
106. ICML 2024Purifying Quantization-conditioned Backdoors via Layer-wise Activation Correction with Distribution Approximation
107. ICML 2024Sharp Rates in Dependent Learning Theory: Avoiding Sample Size Deflation for the Square Loss
108. ICML 2024What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
109. NeurIPS 2024A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness
110. NeurIPS 2024Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
111. NeurIPS 2024Bayes-optimal learning of an extensive-width neural network from quadratically many samples
112. NeurIPS 2024Breaking the curse of dimensionality in structured density estimation
113. NeurIPS 2024Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
114. NeurIPS 2024FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
115. NeurIPS 2024Least Squares Regression Can Exhibit Under-Parameterized Double Descent
116. NeurIPS 2024On Differentially Private U Statistics
117. NeurIPS 2024On the Saturation Effects of Spectral Algorithms in Large Dimensions
118. NeurIPS 2024Optimal Hypothesis Selection in (Almost) Linear Time
119. NeurIPS 2024Robust Mixture Learning when Outliers Overwhelm Small Groups
120. NeurIPS 2024Scalable DBSCAN with Random Projections
121. NeurIPS 2024Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
122. NeurIPS 2024Statistical Multicriteria Benchmarking via the GSD-Front
123. ICLR 2023A Learning Based Hypothesis Test for Harmful Covariate Shift
124. ICLR 2023Don’t fear the unlabelled: safe semi-supervised learning via debiasing
125. ICLR 2023Optimizing Spca-based Continual Learning: A Theoretical Approach
126. ICLR 2023Parametrizing Product Shape Manifolds by Composite Networks
127. ICLR 2023Strong inductive biases provably prevent harmless interpolation
128. ICML 2023Fair Densities via Boosting the Sufficient Statistics of Exponential Families
129. ICML 2023Is Learning Summary Statistics Necessary for Likelihood-free Inference?
130. NeurIPS 2023Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics
131. NeurIPS 2023Multinomial Logistic Regression: Asymptotic Normality on Null Covariates in High-Dimensions
132. NeurIPS 2023Neural Frailty Machine: Beyond proportional hazard assumption in neural survival regressions
133. NeurIPS 2023On Computing Pairwise Statistics with Local Differential Privacy
134. NeurIPS 2023On the Identifiability of Sparse ICA without Assuming Non-Gaussianity
135. NeurIPS 2023On the Statistical Consistency of Risk-Sensitive Bayesian Decision-Making
136. NeurIPS 2023Optimal testing using combined test statistics across independent studies
137. NeurIPS 2023Outlier-Robust Wasserstein DRO
138. NeurIPS 2023Replicable Reinforcement Learning

常见问题

2023–2026 年四大会议一共有多少篇理论 · statistics论文？

共 138 篇，按年份分别是 2023 年 16 篇、2024 年 21 篇、2025 年 44 篇、2026 年 57 篇。

NeurIPS 2026 有多少篇理论 · statistics论文？

NeurIPS 2026 有 12 篇理论 · statistics论文，上一届是 23 篇。

ICLR 2026 有多少篇理论 · statistics论文？

ICLR 2026 有 15 篇理论 · statistics论文，上一届是 7 篇。

ICML 2026 有多少篇理论 · statistics论文？

ICML 2026 有 30 篇理论 · statistics论文，上一届是 13 篇。

CVPR 2025 有多少篇理论 · statistics论文？

CVPR 2025 有 1 篇理论 · statistics论文。

哪个会议的理论 · statistics论文最多？

NeurIPS，2023–2026 年共 58 篇。