通用机器学习 · supervised learning论文趋势 2023–2026
通用机器学习:supervised_learning
统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 1,425 篇被归入该主题的论文。
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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 98 | 45 | 44 | 76 | 263 |
| 2024 | 375 | 41 | 44 | 51 | 511 |
| 2025 | 171 | 40 | 114 | 47 | 372 |
| 2026 | 87 | 48 | 111 | 33 | 279 |
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 41 篇,第 1 / 1 页
- ICLR 2024A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
- ICLR 2024AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
- ICLR 2024Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
- ICLR 2024Efficient Integrators for Diffusion Generative Models
- ICLR 2024Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation
- ICLR 2024Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials
- ICLR 2024Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation
- ICLR 2024Fair Classifiers that Abstain without Harm
- ICLR 2024Faithful and Efficient Explanations for Neural Networks via Neural Tangent Kernel Surrogate Models
- ICLR 2024From Zero to Turbulence: Generative Modeling for 3D Flow Simulation
- ICLR 2024Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
- ICLR 2024Guaranteed Approximation Bounds for Mixed-Precision Neural Operators
- ICLR 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
- ICLR 2024LDReg: Local Dimensionality Regularized Self-Supervised Learning
- ICLR 2024Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation
- ICLR 2024Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
- ICLR 2024Masked Distillation Advances Self-Supervised Transformer Architecture Search
- ICLR 2024Memorization in Self-Supervised Learning Improves Downstream Generalization
- ICLR 2024MgNO: Efficient Parameterization of Linear Operators via Multigrid
- ICLR 2024Mind Your Augmentation: The Key to Decoupling Dense Self-Supervised Learning
- ICLR 2024Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods
- ICLR 2024Modulate Your Spectrum in Self-Supervised Learning
- ICLR 2024Monte Carlo guided Denoising Diffusion models for Bayesian linear inverse problems.
- ICLR 2024Neural Auto-designer for Enhanced Quantum Kernels
- ICLR 2024Neural Fourier Transform: A General Approach to Equivariant Representation Learning
- ICLR 2024Neural Spectral Methods: Self-supervised learning in the spectral domain
- ICLR 2024P2Seg: Pointly-supervised Segmentation via Mutual Distillation
- ICLR 2024PubDef: Defending Against Transfer Attacks From Public Models
- ICLR 2024Rethinking the Uniformity Metric in Self-Supervised Learning
- ICLR 2024Sample-Efficient Linear Representation Learning from Non-IID Non-Isotropic Data
- ICLR 2024Selective Mixup Fine-Tuning for Optimizing Non-Decomposable Objectives
- ICLR 2024Self-supervised Representation Learning from Random Data Projectors
- ICLR 2024SemiReward: A General Reward Model for Semi-supervised Learning
- ICLR 2024Spectrally Transformed Kernel Regression
- ICLR 2024Supervised Knowledge Makes Large Language Models Better In-context Learners
- ICLR 2024The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
- ICLR 2024Towards a statistical theory of data selection under weak supervision
- ICLR 2024Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization
- ICLR 2024Towards the Fundamental Limits of Knowledge Transfer over Finite Domains
- ICLR 2024Vanishing Gradients in Reinforcement Finetuning of Language Models
- ICLR 2024Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data
在 Claude、Cursor 里直接问这个趋势
接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。
可以直接复制这句话问 AI
用 paperlist 查通用机器学习 · supervised learning在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?
AI 会调用的工具:get_topic_stats {"topic": "gml-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。