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 1,424 篇，第 8 / 29 页

351. ICLR 2025Offline Model-Based Optimization by Learning to Rank
352. ICLR 2025Open-CK: A Large Multi-Physics Fields Coupling benchmarks in Combustion Kinetics
353. ICLR 2025PABBO: Preferential Amortized Black-Box Optimization
354. ICLR 2025PIED: Physics-Informed Experimental Design for Inverse Problems
355. ICLR 2025PINP: Physics-Informed Neural Predictor with latent estimation of fluid flows
356. ICLR 2025Re-Evaluating the Impact of Unseen-Class Unlabeled Data on Semi-Supervised Learning Model
357. ICLR 2025RESuM: A Rare Event Surrogate Model for Physics Detector Design
358. ICLR 2025Self-supervised contrastive learning performs non-linear system identification
359. ICLR 2025Spectral-Refiner: Accurate Fine-Tuning of Spatiotemporal Fourier Neural Operator for Turbulent Flows
360. ICLR 2025SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning
361. ICLR 2025SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems
362. ICLR 2025T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data
363. ICLR 2025Towards Self-Supervised Covariance Estimation in Deep Heteroscedastic Regression
364. ICLR 2025Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning
365. ICLR 2025Wasserstein-Regularized Conformal Prediction under General Distribution Shift
366. ICML 2025A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
367. ICML 2025Ab Initio Nonparametric Variable Selection for Scalable Symbolic Regression with Large $p$
368. ICML 2025Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
369. ICML 2025Active Learning with Selective Time-Step Acquisition for PDEs
370. ICML 2025Adaptive Partitioning Schemes for Optimistic Optimization
371. ICML 2025Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
372. ICML 2025An Analysis of Quantile Temporal-Difference Learning
373. ICML 2025Approximately Correct Label Distribution Learning
374. ICML 2025Arbitrarily-Conditioned Multi-Functional Diffusion for Multi-Physics Emulation
375. ICML 2025Balancing the Scales: A Theoretical and Algorithmic Framework for Learning from Imbalanced Data
376. ICML 2025Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
377. ICML 2025BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
378. ICML 2025Calibrated Physics-Informed Uncertainty Quantification
379. ICML 2025Clustering Properties of Self-Supervised Learning
380. ICML 2025Clustering via Self-Supervised Diffusion
381. ICML 2025CoastalBench: A Decade-Long High-Resolution Dataset to Emulate Complex Coastal Processes
382. ICML 2025Collapse-Proof Non-Contrastive Self-Supervised Learning
383. ICML 2025Compressing tree ensembles through Level-wise Optimization and Pruning
384. ICML 2025Concentration Distribution Learning from Label Distributions
385. ICML 2025Confidence Difference Reflects Various Supervised Signals in Confidence-Difference Classification
386. ICML 2025Correlation Clustering Beyond the Pivot Algorithm
387. ICML 2025Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning
388. ICML 2025Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models
389. ICML 2025Deep Electromagnetic Structure Design Under Limited Evaluation Budgets
390. ICML 2025DeepLayout: Learning Neural Representations of Circuit Placement Layout
391. ICML 2025Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning
392. ICML 2025Depth Degeneracy in Neural Networks: Vanishing Angles in Fully Connected ReLU Networks on Initialization
393. ICML 2025Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
394. ICML 2025Disentangling Invariant Subgraph via Variance Contrastive Estimation under Distribution Shifts
395. ICML 2025Divide and Conquer: Learning Label Distribution with Subtasks
396. ICML 2025Does One-shot Give the Best Shot? Mitigating Model Inconsistency in One-shot Federated Learning
397. ICML 2025Enhancing Logits Distillation with Plug&Play Kendall's $\tau$ Ranking Loss
398. ICML 2025Enhancing Target-unspecific Tasks through a Features Matrix
399. ICML 2025EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification
400. ICML 2025ENSUR: Equitable and Statistically Unbiased Recommendation

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。