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 174 篇，第 3 / 4 页

101. ICLR 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
102. ICLR 2024LDReg: Local Dimensionality Regularized Self-Supervised Learning
103. ICLR 2024Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
104. ICLR 2024Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
105. ICLR 2024Masked Distillation Advances Self-Supervised Transformer Architecture Search
106. ICLR 2024Memorization in Self-Supervised Learning Improves Downstream Generalization
107. ICLR 2024MgNO: Efficient Parameterization of Linear Operators via Multigrid
108. ICLR 2024Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
109. ICLR 2024Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
110. ICLR 2024Modulate Your Spectrum in Self-Supervised Learning
111. ICLR 2024Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.
112. ICLR 2024Neural Auto-designer for Enhanced Quantum Kernels
113. ICLR 2024Neural Fourier Transform: A General Approach to Equivariant Representation Learning
114. ICLR 2024Neural Spectral Methods: Self-supervised learning in the spectral domain
115. ICLR 2024P2Seg: Pointly-supervised Segmentation via Mutual Distillation
116. ICLR 2024PubDef: Defending Against Transfer Attacks From Public Models
117. ICLR 2024Rethinking the Uniformity Metric in Self-Supervised Learning
118. ICLR 2024Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
119. ICLR 2024Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
120. ICLR 2024Self-supervised Representation Learning from Random Data Projectors
121. ICLR 2024SemiReward: A General Reward Model for Semi-supervised Learning
122. ICLR 2024Spectrally Transformed Kernel Regression
123. ICLR 2024Supervised Knowledge Makes Large Language Models Better In-context Learners
124. ICLR 2024The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
125. ICLR 2024Towards a statistical theory of data selection under weak supervision
126. ICLR 2024Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization
127. ICLR 2024Towards the Fundamental Limits of Knowledge Transfer over Finite Domains
128. ICLR 2024Vanishing Gradients in Reinforcement Finetuning of Language Models
129. ICLR 2024Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data
130. ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
131. ICLR 2023A theoretical study of inductive biases in contrastive learning
132. ICLR 2023Agnostic Learning of General ReLU Activation Using Gradient Descent
133. ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
134. ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
135. ICLR 2023Don’t fear the unlabelled: safe semi-supervised learning via debiasing
136. ICLR 2023EA-HAS-Bench: Energy-aware Hyperparameter and Architecture Search Benchmark
137. ICLR 2023Effective Self-supervised Pre-training on Low-compute Networks without Distillation
138. ICLR 2023Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems
139. ICLR 2023Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders
140. ICLR 2023FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
141. ICLR 2023Guiding continuous operator learning through Physics-based boundary constraints
142. ICLR 2023How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study
143. ICLR 2023HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork
144. ICLR 2023Identifiability Results for Multimodal Contrastive Learning
145. ICLR 2023Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
146. ICLR 2023InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
147. ICLR 2023Label Propagation with Weak Supervision
148. ICLR 2023Learning Controllable Adaptive Simulation for Multi-resolution Physics
149. ICLR 2023Minimax Optimal Kernel Operator Learning via Multilevel Training
150. ICLR 2023MocoSFL: enabling cross-client collaborative self-supervised learning

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。