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 114 篇,第 1 / 3 页
- ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
- ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
- ICML 2025Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
- ICML 2025Active Learning with Selective Time-Step Acquisition for PDEs
- ICML 2025Adaptive Partitioning Schemes for Optimistic Optimization
- ICML 2025Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
- ICML 2025An Analysis of Quantile Temporal-Difference Learning
- ICML 2025Approximately Correct Label Distribution Learning
- ICML 2025Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
- ICML 2025Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
- ICML 2025Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
- ICML 2025BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
- ICML 2025Calibrated Physics-Informed Uncertainty Quantification
- ICML 2025Clustering Properties of Self-Supervised Learning
- ICML 2025Clustering via Self-Supervised Diffusion
- ICML 2025CoastalBench: A Decade-Long High-Resolution Dataset to Emulate Complex Coastal Processes
- ICML 2025Collapse-Proof Non-Contrastive Self-Supervised Learning
- ICML 2025Compressing tree ensembles through Level-wise Optimization and Pruning
- ICML 2025Concentration Distribution Learning from Label Distributions
- ICML 2025Confidence Difference Reflects Various Supervised Signals in Confidence-Difference Classification
- ICML 2025Correlation Clustering Beyond the Pivot Algorithm
- ICML 2025Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning
- ICML 2025Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models
- ICML 2025Deep Electromagnetic Structure Design Under Limited Evaluation Budgets
- ICML 2025DeepLayout: Learning Neural Representations of Circuit Placement Layout
- ICML 2025Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
- ICML 2025Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization
- ICML 2025Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
- ICML 2025Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
- ICML 2025Divide and Conquer: Learning Label Distribution with Subtasks
- ICML 2025Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
- ICML 2025Enhancing Logits Distillation with Plug&Play Kendall's $\tau$ Ranking Loss
- ICML 2025Enhancing Target-unspecific Tasks through a Features Matrix
- ICML 2025EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification
- ICML 2025ENSUR: Equitable and Statistically Unbiased Recommendation
- ICML 2025Equivalence is All: A Unified View for Self-supervised Graph Learning
- ICML 2025FedClean: A General Robust Label Noise Correction for Federated Learning
- ICML 2025FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
- ICML 2025Focal-SAM: Focal Sharpness-Aware Minimization for Long-Tailed Classification
- 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
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。