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 44 篇，第 1 / 1 页

1. ICML 2024A General Framework for Learning from Weak Supervision
2. ICML 2024A New Branch-and-Bound Pruning Framework for $\ell_0$-Regularized Problems
3. ICML 2024A Sober Look at LLMs for Material Discovery: Are They Actually Good for Bayesian Optimization Over Molecules?
4. ICML 2024A3S: A General Active Clustering Method with Pairwise Constraints
5. ICML 2024Be Your Own Neighborhood: Detecting Adversarial Examples by the Neighborhood Relations Built on Self-Supervised Learning
6. ICML 2024Binary Decomposition: A Problem Transformation Perspective for Open-Set Semi-Supervised Learning
7. ICML 2024Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
8. ICML 2024Boosting Offline Optimizers with Surrogate Sensitivity
9. ICML 2024Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation
10. ICML 2024Compress Clean Signal from Noisy Raw Image: A Self-Supervised Approach
11. ICML 2024Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
12. ICML 2024ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy
13. ICML 2024Correlation-Induced Label Prior for Semi-Supervised Multi-Label Learning
14. ICML 2024Counterfactual Metarules for Local and Global Recourse
15. ICML 2024Deep Stochastic Mechanics
16. ICML 2024Efficient Black-box Adversarial Attacks via Bayesian Optimization Guided by a Function Prior
17. ICML 2024Enhancing Trajectory Prediction through Self-Supervised Waypoint Distortion Prediction
18. ICML 2024Equivariant Graph Neural Operator for Modeling 3D Dynamics
19. ICML 2024Exploring Correlations of Self-Supervised Tasks for Graphs
20. ICML 2024FedSC: Provable Federated Self-supervised Learning with Spectral Contrastive Objective over Non-i.i.d. Data
21. ICML 2024From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble
22. ICML 2024Hierarchical Neural Operator Transformer with Learnable Frequency-aware Loss Prior for Arbitrary-scale Super-resolution
23. ICML 2024High-Dimensional Bayesian Optimization via Semi-Supervised Learning with Optimized Unlabeled Data Sampling
24. ICML 2024Implicit Representations via Operator Learning
25. ICML 2024Improved Operator Learning by Orthogonal Attention
26. ICML 2024In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
27. ICML 2024Information Flow in Self-Supervised Learning
28. ICML 2024Learning Surrogates for Offline Black-Box Optimization via Gradient Matching
29. ICML 2024MALIBO: Meta-learning for Likelihood-free Bayesian Optimization
30. ICML 2024Neural Operators with Localized Integral and Differential Kernels
31. ICML 2024OTMatch: Improving Semi-Supervised Learning with Optimal Transport
32. ICML 2024OxyGenerator: Reconstructing Global Ocean Deoxygenation Over a Century with Deep Learning
33. ICML 2024Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
34. ICML 2024Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
35. ICML 2024Scribble-Supervised Semantic Segmentation with Prototype-based Feature Augmentation
36. ICML 2024Self-Supervised Coarsening of Unstructured Grid with Automatic Differentiation
37. ICML 2024Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
38. ICML 2024SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification
39. ICML 2024Towards Realistic Model Selection for Semi-supervised Learning
40. ICML 2024Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
41. ICML 2024Unveiling the Dynamics of Information Interplay in Supervised Learning
42. ICML 2024UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis
43. ICML 2024Vectorized Conditional Neural Fields: A Framework for Solving Time-dependent Parametric Partial Differential Equations
44. ICML 2024Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation

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。