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 45 篇,第 1 / 1 页
- ICLR 2023A General Framework For Proving The Equivariant Strong Lottery Ticket Hypothesis
- ICLR 2023A theoretical study of inductive biases in contrastive learning
- ICLR 2023Agnostic Learning of General ReLU Activation Using Gradient Descent
- ICLR 2023Coupled Multiwavelet Operator Learning for Coupled Differential Equations
- ICLR 2023Deep Ranking Ensembles for Hyperparameter Optimization
- ICLR 2023Don’t fear the unlabelled: safe semi-supervised learning via debiasing
- ICLR 2023EA-HAS-Bench: Energy-aware Hyperparameter and Architecture Search Benchmark
- ICLR 2023Effective Self-supervised Pre-training on Low-compute Networks without Distillation
- ICLR 2023Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems
- ICLR 2023Exploring The Role of Mean Teachers in Self-supervised Masked Auto-Encoders
- ICLR 2023FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
- ICLR 2023Guiding continuous operator learning through Physics-based boundary constraints
- ICLR 2023How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study
- ICLR 2023HyperDeepONet: learning operator with complex target function space using the limited resources via hypernetwork
- ICLR 2023Identifiability Results for Multimodal Contrastive Learning
- ICLR 2023Imbalanced Semi-supervised Learning with Bias Adaptive Classifier
- ICLR 2023InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning
- ICLR 2023Label Propagation with Weak Supervision
- ICLR 2023Learning Controllable Adaptive Simulation for Multi-resolution Physics
- ICLR 2023Minimax Optimal Kernel Operator Learning via Multilevel Training
- ICLR 2023MocoSFL: enabling cross-client collaborative self-supervised learning
- ICLR 2023No Reason for No Supervision: Improved Generalization in Supervised Models
- ICLR 2023Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities
- ICLR 2023On the Effectiveness of Out-of-Distribution Data in Self-Supervised Long-Tail Learning.
- ICLR 2023One Transformer Can Understand Both 2D & 3D Molecular Data
- ICLR 2023Planckian Jitter: countering the color-crippling effects of color jitter on self-supervised training
- ICLR 2023Progressively Compressed Auto-Encoder for Self-supervised Representation Learning
- ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
- ICLR 2023Sampling-based inference for large linear models, with application to linearised Laplace
- ICLR 2023Sampling-free Inference for Ab-Initio Potential Energy Surface Networks
- ICLR 2023Self-Supervised Category-Level Articulated Object Pose Estimation with Part-Level SE(3) Equivariance
- ICLR 2023Self-supervised learning with rotation-invariant kernels
- ICLR 2023Semi-supervised learning with a principled likelihood from a generative model of data curation
- ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
- ICLR 2023SoftMatch: Addressing the Quantity-Quality Tradeoff in Semi-supervised Learning
- ICLR 2023Spectral Augmentation for Self-Supervised Learning on Graphs
- ICLR 2023Symmetric Pruning in Quantum Neural Networks
- ICLR 2023Temperature Schedules for self-supervised contrastive methods on long-tail data
- ICLR 2023The hidden uniform cluster prior in self-supervised learning
- ICLR 2023Towards the Generalization of Contrastive Self-Supervised Learning
- ICLR 2023Transformer Meets Boundary Value Inverse Problems
- ICLR 2023Unbiased Supervised Contrastive Learning
- ICLR 2023Understanding The Robustness of Self-supervised Learning Through Topic Modeling
- ICLR 2023Weighted Ensemble Self-Supervised Learning
- ICLR 2023What shapes the loss landscape of self supervised learning?
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。