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 58 篇，第 1 / 2 页

1. NeurIPS 2026Asymptotic Anytime-Valid Inference for U-statistics
2. NeurIPS 2026Computationally sufficient statistics for Ising models
3. NeurIPS 2026Hierarchical Concept Geometry in Language Representations Emerges from Word Co-occurrence
4. NeurIPS 2026Neural population tuning statistics as priors for multitask generalization
5. NeurIPS 2026Pretraining Data Statistics Shape the Phases of Learning Entity Comparison in Language Models
6. NeurIPS 2026Probabilistic Signature Inversion: Learning Conditional Distributions from Truncated Signatures
7. NeurIPS 2026Rare-Tail Statistics For Learning Biased Gaussian Halfspaces with Label Noise
8. NeurIPS 2026Subcritical Signal Propagation at Initialization in Normalization-Free Transformers
9. NeurIPS 2026Symmetry Guarantees Statistic Recovery in Variational Inference
10. NeurIPS 2026TopoFisher: Learning Topological Summary Statistics by Maximizing Fisher Information
11. NeurIPS 2026What Transformer FFNs Never See: Theory, Diagnosis, and Lightweight Remediation
12. NeurIPS 2026Your Self-Supervised Projection Head Captures Object Co-Occurrence Statistics
13. NeurIPS 2025A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
14. NeurIPS 2025Backward Conformal Prediction
15. NeurIPS 2025Bivariate Matrix-valued Linear Regression (BMLR): Finite-sample performance under Identifiability and Sparsity Assumptions
16. NeurIPS 2025Co-Regularization Enhances Knowledge Transfer in High Dimensions
17. NeurIPS 2025Comparison requires valid measurement: Rethinking attack success rate comparisons in AI red teaming
18. NeurIPS 2025Demystifying Spectral Feature Learning for Instrumental Variable Regression
19. NeurIPS 2025Estimation of Stochastic Optimal Transport Maps
20. NeurIPS 2025Improved Robust Estimation for Erdős-Rényi Graphs: The Sparse Regime and Optimal Breakdown Point
21. NeurIPS 2025Information-Computation Tradeoffs for Noiseless Linear Regression with Oblivious Contamination
22. NeurIPS 2025Integral Imprecise Probability Metrics
23. NeurIPS 2025Non-Asymptotic Analysis Of Data Augmentation For Precision Matrix Estimation
24. NeurIPS 2025On the Emergence of Linear Analogies in Word Embeddings
25. NeurIPS 2025Optimal and Provable Calibration in High-Dimensional Binary Classification: Angular Calibration and Platt Scaling
26. NeurIPS 2025Private Statistical Estimation via Truncation
27. NeurIPS 2025Product Distribution Learning with Imperfect Advice
28. NeurIPS 2025Robust Estimation Under Heterogeneous Corruption Rates
29. NeurIPS 2025Small Resamples, Sharp Guarantees: Convergence Rates for Resampled Studentized Quantile Estimators
30. NeurIPS 2025STAR-Bets: Sequential TArget-Recalculating Bets for Tighter Confidence Intervals
31. NeurIPS 2025Statistical Inference for Gradient Boosting Regression
32. NeurIPS 2025Statistical Inference under Performativity
33. NeurIPS 2025Stochastic Gradients under Nuisances
34. NeurIPS 2025The Price of Sparsity: Sufficient Conditions for Sparse Recovery using Sparse and Sparsified Measurements
35. NeurIPS 2025Tight Asymptotics of Extreme Order Statistics
36. NeurIPS 2024A Pairwise Pseudo-likelihood Approach for Matrix Completion with Informative Missingness
37. NeurIPS 2024Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
38. NeurIPS 2024Bayes-optimal learning of an extensive-width neural network from quadratically many samples
39. NeurIPS 2024Breaking the curse of dimensionality in structured density estimation
40. NeurIPS 2024Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers
41. NeurIPS 2024FedGTST: Boosting Global Transferability of Federated Models via Statistics Tuning
42. NeurIPS 2024Least Squares Regression Can Exhibit Under-Parameterized Double Descent
43. NeurIPS 2024On Differentially Private U Statistics
44. NeurIPS 2024On the Saturation Effects of Spectral Algorithms in Large Dimensions
45. NeurIPS 2024Optimal Hypothesis Selection in (Almost) Linear Time
46. NeurIPS 2024Robust Mixture Learning when Outliers Overwhelm Small Groups
47. NeurIPS 2024Scalable DBSCAN with Random Projections
48. NeurIPS 2024Semi-Supervised Sparse Gaussian Classification: Provable Benefits of Unlabeled Data
49. NeurIPS 2024Statistical Multicriteria Benchmarking via the GSD-Front
50. NeurIPS 2023Fast Online Changepoint Detection via Functional Pruning CUSUM Statistics

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。