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 111 篇，第 1 / 3 页

1. ICML 2026$\mathbb{R}^{2k}$ is Theoretically Large Enough for Embedding-based Top-$k$ Retrieval
2. ICML 2026A Minimax Approach for Optimal Intervention Policy Learning with Two-Stage Outcomes
3. ICML 2026Active Budget Allocation for Efficient Scaling Law Estimation via Surrogate-Guided Pruning
4. ICML 2026Adaptive Physics Transformer with Fused Global-Local Attention for Subsurface Energy Systems
5. ICML 2026Advancing Analytic Class-Incremental Learning through Vision-Language Calibration
6. ICML 2026Adversarial Robustness of Implicit Neural Representation-Based Classifiers
7. ICML 2026AES: Curing Optimizer Blindness in Long-Tailed Recognition via State-Aware Correction
8. ICML 2026Amortized Variational Inference for Partial-Label Learning: A Probabilistic Approach to Label Disambiguation
9. ICML 2026Approximation Preserving Coresets
10. ICML 2026Beyond Accuracy and Complexity: The Effective Information Criterion for Structurally Stable Symbolic Regression
11. ICML 2026Beyond Distribution Estimation: Simplex Anchored Structural Inference Towards Universal Semi-Supervised Learning
12. ICML 2026Beyond Magnitude: Scale-Invariant Evidential Fusion for Multi-View Classification
13. ICML 2026Bio-Inspired Self-Supervised Learning for Wrist-worn Accelerometer Data
14. ICML 2026BTSP-CAM: A Brain-Inspired Geometric Memory for Class-Incremental Learning
15. ICML 2026Can local learning match self-supervised backpropagation?
16. ICML 2026Characterization of Gaussian Universality Breakdown in High-Dimensional Empirical Risk Minimization
17. ICML 2026CINOC: Cardinality-Invariant Neural Operator Policies for Scalable PDE Control
18. ICML 2026Class-Prior Perturbation-Robust Regularization for Imbalanced Unreliable Partial Label Learning
19. ICML 2026CLoVE: Personalized Federated Learning through Clustering of Loss Vector Embeddings
20. ICML 2026CoEvol-NO: State and Coordinate Co-Evolution with an Error-Driven Predictor-Corrector Paradigm for Neural Operator Transformer
21. ICML 2026Collaborative Learning for Semi-Supervised LiDAR Semantic Segmentation
22. ICML 2026Continuous-Time Piecewise-Linear Recurrent Neural Networks
23. ICML 2026Contrastive Order Learning: A General Framework for Ordinal Regression
24. ICML 2026CREDIT: Certified Ownership Verification of Deep Neural Networks Against Model Extraction Attacks
25. ICML 2026Cross-View Lewis Weight Fusion Empowering Exemplar Replay for Federated Class-Incremental Learning
26. ICML 2026DART: Distribution-Aware Adaptive Relational Transfer for Adversarial Attacks against Closed-Source MLLMs
27. ICML 2026Di-BiLPS: Denoising induced Bidirectional Latent-PDE-Solver under Sparse Observations
28. ICML 2026DiL: Discrete-anchored Representation Alignment for Semi-Supervised Continual Learning
29. ICML 2026Diversity-Driven Offline Multi-Objective Optimization via Nested Pareto Set Learning
30. ICML 2026Divisiveness-Consistent Label Distribution Learning
31. ICML 2026Do Neural Operators Forget Geometry? The Forgetting Hypothesis in Deep Operator Learning
32. ICML 2026ECSEL: Explainable Classification via Signomial Equation Learning
33. ICML 2026Ekka: Automated Diagnosis of Silent Errors in LLM Inference
34. ICML 2026Enhancing Cross-subject Emotion Recognition via Heterogeneous Distribution Augmentation and Collaborative Learning
35. ICML 2026Equivariant Neural Networks for General Linear Symmetries on Lie Algebras
36. ICML 2026Euler–Poincaré Neural Dynamics: A Geometric-Mechanics Framework for Scientific Simulation
37. ICML 2026FairMerging: Rethinking Model Merging through the Lens of Fairness
38. ICML 2026Federated Data and Feature Selection by Generalized CUR Decomposition
39. ICML 2026FedReLa: Imbalanced Federated Learning via Re-Labeling
40. ICML 2026Fix the Loss, Not the Radius: Rethinking the Adversarial Perturbation of Sharpness-Aware Minimization
41. ICML 2026Flowers: A Warp Drive for Neural PDE Solvers
42. ICML 2026Fractional is Better: Learnable Derivative Orders in Neural Operator Learning
43. ICML 2026From Basis to Basis: Gaussian Particle Representation for Interpretable PDE Operators
44. ICML 2026Functional Attention: From Pairwise Affinities to Functional Correspondences
45. ICML 2026Generative Neural Operators through Diffusion Last Layer
46. ICML 2026Identifying Common Hubs in Multiple Gaussian Graphical Models
47. ICML 2026IdEst: Assessing Self-Supervised Learning Representations via Intrinsic Dimension
48. ICML 2026Impact of Connectivity on Laplacian Representations in Reinforcement Learning
49. ICML 2026Imposing Boundary Conditions on Neural Operators via Learned Function Extensions
50. ICML 2026Kronecker Generative Networks: A General Neural Architecture for Parameter-Efficient Learning Across Classification Tasks

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。