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 313 篇,第 4 / 7 页
- ICML 2025From Logits to Hierarchies: Hierarchical Clustering made Simple
- ICML 2025Generalized additive models via direct optimization of regularized decision stump forests
- ICML 2025Generalized Random Forests Using Fixed-Point Trees
- ICML 2025Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning
- ICML 2025Gradient Aligned Regression via Pairwise Losses
- ICML 2025HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEs
- ICML 2025HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal Transport
- ICML 2025Holistic Physics Solver: Learning PDEs in a Unified Spectral-Physical Space
- ICML 2025Human Cognition-Inspired Hierarchical Fuzzy Learning Machine
- ICML 2025Hyperband-based Bayesian Optimization for Black-box Prompt Selection
- ICML 2025Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
- ICML 2025Improving Multi-Class Calibration through Normalization-Aware Isotonic Techniques
- ICML 2025Instance Correlation Graph-based Naive Bayes
- ICML 2025Label Distribution Propagation-based Label Completion for Crowdsourcing
- ICML 2025LADA: Scalable Label-Specific CLIP Adapter for Continual Learning
- ICML 2025Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification
- ICML 2025Learning from True-False Labels via Multi-modal Prompt Retrieving
- ICML 2025Learning Imbalanced Data with Beneficial Label Noise
- ICML 2025Learning Monotonic Probabilities with a Generative Cost Model
- ICML 2025Lightweight Dataset Pruning without Full Training via Example Difficulty and Prediction Uncertainty
- ICML 2025M2PDE: Compositional Generative Multiphysics and Multi-component PDE Simulation
- ICML 2025MetricEmbedding: Accelerate Metric Nearness by Tropical Inner Product
- ICML 2025MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
- ICML 2025Modified K-means Algorithm with Local Optimality Guarantees
- ICML 2025MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
- ICML 2025Multivariate Conformal Selection
- ICML 2025Non-Stationary Predictions May Be More Informative: Exploring Pseudo-Labels with a Two-Phase Pattern of Training Dynamics
- ICML 2025Not all solutions are created equal: An analytical dissociation of functional and representational similarity in deep linear neural networks
- ICML 2025On the Benefits of Active Data Collection in Operator Learning
- ICML 2025On the Importance of Embedding Norms in Self-Supervised Learning
- ICML 2025On the Out-of-Distribution Generalization of Self-Supervised Learning
- ICML 2025Optimization for Neural Operators can Benefit from Width
- ICML 2025Overcoming the Curse of Dimensionality in Reinforcement Learning Through Approximate Factorization
- ICML 2025Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms
- ICML 2025Position: A Critical Perspective on The Value in Studying Deep Learning Phenomena
- ICML 2025Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
- ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
- ICML 2025Prediction models that learn to avoid missing values
- ICML 2025Predictive Performance of Deep Quantum Data Re-uploading Models
- ICML 2025Preserving AUC Fairness in Learning with Noisy Protected Groups
- ICML 2025Principled Algorithms for Optimizing Generalized Metrics in Binary Classification
- ICML 2025Provably Efficient RL for Linear MDPs under Instantaneous Safety Constraints in Non-Convex Feature Spaces
- ICML 2025Quantum Optimization via Gradient-Based Hamiltonian Descent
- ICML 2025Random Feature Representation Boosting
- ICML 2025Rank-One Modified Value Iteration
- ICML 2025Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL
- ICML 2025Right Time to Learn: Promoting Generalization via Bio-inspired Spacing Effect in Knowledge Distillation
- ICML 2025Robust Automatic Modulation Classification with Fuzzy Regularization
- ICML 2025Safety Certificate against Latent Variables with Partially Unidentifiable Dynamics
- ICML 2025scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell 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。