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 2 / 2 页

51. NeurIPS 2023Label-efficient Segmentation via Affinity Propagation
52. NeurIPS 2023Learning Fine-grained View-Invariant Representations from Unpaired Ego-Exo Videos via Temporal Alignment
53. NeurIPS 2023Learning From Biased Soft Labels
54. NeurIPS 2023Learning Interpretable Low-dimensional Representation via Physical Symmetry
55. NeurIPS 2023Lo-Hi: Practical ML Drug Discovery Benchmark
56. NeurIPS 2023Low-shot Object Learning with Mutual Exclusivity Bias
57. NeurIPS 2023Machine learning detects terminal singularities
58. NeurIPS 2023Managing Temporal Resolution in Continuous Value Estimation: A Fundamental Trade-off
59. NeurIPS 2023Masked Image Residual Learning for Scaling Deeper Vision Transformers
60. NeurIPS 2023Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
61. NeurIPS 2023Metis: Understanding and Enhancing In-Network Regular Expressions
62. NeurIPS 2023Minimum-Risk Recalibration of Classifiers
63. NeurIPS 2023Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-Encoder
64. NeurIPS 2023Navigating Data Heterogeneity in Federated Learning: A Semi-Supervised Federated Object Detection
65. NeurIPS 2023No Representation Rules Them All in Category Discovery
66. NeurIPS 2023On Separate Normalization in Self-supervised Transformers
67. NeurIPS 2023On the Exploitability of Instruction Tuning
68. NeurIPS 2023On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training
69. NeurIPS 2023OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning
70. NeurIPS 2023Optimal Block-wise Asymmetric Graph Construction for Graph-based Semi-supervised Learning
71. NeurIPS 2023Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage
72. NeurIPS 2023PETAL: Physics Emulation Through Averaged Linearizations for Solving Inverse Problems
73. NeurIPS 2023Relax, it doesn’t matter how you get there: A new self-supervised approach for multi-timescale behavior analysis
74. NeurIPS 2023Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
75. NeurIPS 2023RevColV2: Exploring Disentangled Representations in Masked Image Modeling
76. NeurIPS 2023RGMIL: Guide Your Multiple-Instance Learning Model with Regressor
77. NeurIPS 2023Robust and Actively Secure Serverless Collaborative Learning
78. NeurIPS 2023Safety Verification of Decision-Tree Policies in Continuous Time
79. NeurIPS 2023SALSA VERDE: a machine learning attack on LWE with sparse small secrets
80. NeurIPS 2023Sample based Explanations via Generalized Representers
81. NeurIPS 2023Self-Supervised Learning of Representations for Space Generates Multi-Modular Grid Cells
82. NeurIPS 2023Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
83. NeurIPS 2023Self-Supervised Motion Magnification by Backpropagating Through Optical Flow
84. NeurIPS 2023Self-supervised Object-Centric Learning for Videos
85. NeurIPS 2023Self-Supervised Reinforcement Learning that Transfers using Random Features
86. NeurIPS 2023Self-Supervised Visual Acoustic Matching
87. NeurIPS 2023Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
88. NeurIPS 2023Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition
89. NeurIPS 2023Switching Temporary Teachers for Semi-Supervised Semantic Segmentation
90. NeurIPS 2023Tanimoto Random Features for Scalable Molecular Machine Learning
91. NeurIPS 2023The Rashomon Importance Distribution: Getting RID of Unstable, Single Model-based Variable Importance
92. NeurIPS 2023Towards Generic Semi-Supervised Framework for Volumetric Medical Image Segmentation
93. NeurIPS 2023Transfer Learning with Affine Model Transformation
94. NeurIPS 2023Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data
95. NeurIPS 2023UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition
96. NeurIPS 2023Uncovering the Hidden Dynamics of Video Self-supervised Learning under Distribution Shifts
97. NeurIPS 2023Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems
98. NeurIPS 2023Waypoint Transformer: Reinforcement Learning via Supervised Learning with Intermediate Targets

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。