通用机器学习 · supervised learning论文趋势 2023–2026

主要结论

• 通用机器学习 · supervised learning论文从 2023 年的 263 篇增长到 2026 年的 279 篇，三年间扩大到约 1.1 倍。
• NeurIPS 是发通用机器学习 · supervised learning论文最多的会议，2023–2026 年共 731 篇，占四个会议总量的 51%。
• 交叉方向里涨得最快的是扩散模型：同时属于两个主题的论文从 2023 年的 2 篇增至 2026 年的 9 篇。
• 在「通用机器学习」的 6 个主题里，它的 2026 年论文数排第 3；同组增长最快的通用机器学习 · evaluation是 4.3 倍，通用机器学习 · supervised learning是 1.1 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 2026AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training
• ICML 2026$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
• ICLR 2026Adaptive Concept Discovery for Interpretable Few-Shot Text Classification
• CVPR 2026Enabling Supervised Learning of Generative Signatures for Generalized AI-Generated Images
• NeurIPS 2025$\boldsymbol{\lambda}$-Orthogonality Regularization for Compatible Representation Learning
• ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
• ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
• CVPR 2025A Unified Framework for Heterogeneous Semi-supervised Learning
• NeurIPS 2024(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning
• ICML 2024A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
• ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
• CVPR 2024Efficient Hyperparameter Optimization with Adaptive Fidelity Identification
• NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
• ICML 2023A Model-free Closeness-of-influence Test for Features in Supervised Learning
• ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
• CVPR 2023Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data
• NeurIPS 2026Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
• ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
• ICLR 2026Buckingham $\pi$-Invariant Test‑Time Projection for Robust PDE Surrogate Modeling
• CVPR 2026HyperNAS Enhancing Architecture Representation for NAS Predictor via Hypernetwork

全部通用机器学习 · supervised learning论文

共 98 篇，第 1 / 2 页

1. NeurIPS 2023A General Framework for Equivariant Neural Networks on Reductive Lie Groups
2. NeurIPS 2023A General Framework for Robust G-Invariance in G-Equivariant Networks
3. NeurIPS 2023A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning
4. NeurIPS 2023A Unified Approach to Count-Based Weakly Supervised Learning
5. NeurIPS 2023AdaptSSR: Pre-training User Model with Augmentation-Adaptive Self-Supervised Ranking
6. NeurIPS 2023Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
7. NeurIPS 2023An Adaptive Algorithm for Learning with Unknown Distribution Drift
8. NeurIPS 2023Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methods
9. NeurIPS 2023Asymptotics of Bayesian Uncertainty Estimation in Random Features Regression
10. NeurIPS 2023Binary Classification with Confidence Difference
11. NeurIPS 2023Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
12. NeurIPS 2023CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning
13. NeurIPS 2023Can semi-supervised learning use all the data effectively? A lower bound perspective
14. NeurIPS 2023CAPro: Webly Supervised Learning with Cross-modality Aligned Prototypes
15. NeurIPS 2023Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
16. NeurIPS 2023Class-Distribution-Aware Pseudo-Labeling for Semi-Supervised Multi-Label Learning
17. NeurIPS 2023ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
18. NeurIPS 2023Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering
19. NeurIPS 2023Combating Representation Learning Disparity with Geometric Harmonization
20. NeurIPS 2023Conditional independence testing under misspecified inductive biases
21. NeurIPS 2023Covariance-adaptive best arm identification
22. NeurIPS 2023Cross-Scale MAE: A Tale of Multiscale Exploitation in Remote Sensing
23. NeurIPS 2023Curriculum Learning With Infant Egocentric Videos
24. NeurIPS 2023DAW: Exploring the Better Weighting Function for Semi-supervised Semantic Segmentation
25. NeurIPS 2023Distributional Policy Evaluation: a Maximum Entropy approach to Representation Learning
26. NeurIPS 2023Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised Learning
27. NeurIPS 2023Doubly-Robust Self-Training
28. NeurIPS 2023DropPos: Pre-Training Vision Transformers by Reconstructing Dropped Positions
29. NeurIPS 2023Dynamo-Depth: Fixing Unsupervised Depth Estimation for Dynamical Scenes
30. NeurIPS 2023Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes
31. NeurIPS 2023Effective Targeted Attacks for Adversarial Self-Supervised Learning
32. NeurIPS 2023End-to-End Meta-Bayesian Optimisation with Transformer Neural Processes
33. NeurIPS 2023Equal Opportunity of Coverage in Fair Regression
34. NeurIPS 2023Error Bounds for Learning with Vector-Valued Random Features
35. NeurIPS 2023Ess-InfoGAIL: Semi-supervised Imitation Learning from Imbalanced Demonstrations
36. NeurIPS 2023Explaining Predictive Uncertainty with Information Theoretic Shapley Values
37. NeurIPS 2023Exponentially Convergent Algorithms for Supervised Matrix Factorization
38. NeurIPS 2023Fair, Polylog-Approximate Low-Cost Hierarchical Clustering
39. NeurIPS 2023Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
40. NeurIPS 2023FLSL: Feature-level Self-supervised Learning
41. NeurIPS 2023Generalized Semi-Supervised Learning via Self-Supervised Feature Adaptation
42. NeurIPS 2023Human-Aligned Calibration for AI-Assisted Decision Making
43. NeurIPS 2023Identifiable Contrastive Learning with Automatic Feature Importance Discovery
44. NeurIPS 2023Implicit Contrastive Representation Learning with Guided Stop-gradient
45. NeurIPS 2023Implicit variance regularization in non-contrastive SSL
46. NeurIPS 2023Improving Self-supervised Molecular Representation Learning using Persistent Homology
47. NeurIPS 2023Incentives in Private Collaborative Machine Learning
48. NeurIPS 2023InstanT: Semi-supervised Learning with Instance-dependent Thresholds
49. NeurIPS 2023Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation
50. NeurIPS 2023Koopman Kernel Regression

常见问题

2023–2026 年四大会议一共有多少篇通用机器学习 · supervised learning论文？

共 1,425 篇，按年份分别是 2023 年 263 篇、2024 年 511 篇、2025 年 372 篇、2026 年 279 篇。

NeurIPS 2026 有多少篇通用机器学习 · supervised learning论文？

NeurIPS 2026 有 87 篇通用机器学习 · supervised learning论文，上一届是 171 篇。

ICLR 2026 有多少篇通用机器学习 · supervised learning论文？

ICLR 2026 有 48 篇通用机器学习 · supervised learning论文，上一届是 40 篇。

ICML 2026 有多少篇通用机器学习 · supervised learning论文？

ICML 2026 有 111 篇通用机器学习 · supervised learning论文，上一届是 114 篇。

CVPR 2026 有多少篇通用机器学习 · supervised learning论文？

CVPR 2026 有 33 篇通用机器学习 · supervised learning论文，上一届是 47 篇。

哪个会议的通用机器学习 · supervised learning论文最多？

NeurIPS，2023–2026 年共 731 篇。